Thermographic inspection techniques

ABSTRACT

A system may include a source of dry ice, a thermal camera, and a computing device. The computing device may be configured to control the source of dry ice to cause dry ice to be introduced into an internal passage of a tested component. The tested component may include debris within the internal passage, and the dry ice may remove at least some of the debris from the internal passage. The computing device also may be configured to receive, from the thermal camera, thermographic image data representative of the thermal response of the tested component and output a representation based on the thermographic image data.

This application claims the benefit of U.S. Provisional Application No.61/912,946, filed Dec. 6, 2013, which is incorporated herein byreference in its entirety.

TECHNICAL FIELD

The disclosure relates to thermographic inspection.

BACKGROUND

Nondestructive testing of components may be used to identify anomalies,defects, or damaged portions of components without further damaging thecomponent. One type of nondestructive testing is thermography. Inthermography, a thermal camera is used to capture image datarepresentative of a surface temperature of a component in response to anapplied heat or cooling source. In flash thermography, a heat source,such as a flash lamp, is used to apply heat to the outer surface of thecomponent. The thermal camera captures image data representative of thesurface temperature of the component over time, which provides thethermal response of the component to the heat source. In flowingthermography, a fluid (e.g., hotter or colder than the bulk temperatureof the component) is flowed through internal passages of the component,and the thermal camera captures image data representative of the surfacetemperature of the component over time.

SUMMARY

The disclosure describes various techniques for non-destructivelytesting a component using thermography. In some examples, a testedcomponent may be tested using flowing thermography. A thermal camera maycapture image data during the flowing thermography test. A computingdevice may receive the image data and flow rate data measured by atleast one flow meter during, prior to, or after the flowing thermographytest. The computing device may associate flow values with the image databased on the flow rate data to generate quantitative flowingthermography image data. In this way, the image data captured by thethermal camera may provide quantitative indicators of the flow ratethrough internal passages of the tested component. The quantitativeindicators may be used (e.g., by the computing device or a trainedtechnician) to determine whether the flow of fluid through the internalpassages is within or outside a predetermined range, e.g., a designrange.

In some examples, a tested component may be tested using flowingthermography, flash thermography, or both. During the thermographictesting, the thermal camera may capture infrared data in the form oftwo-dimensional image data. In accordance with these examples, acomputing device may receive the two-dimensional image data may morphthe two-dimensional image data to substantially match master image data.The master image data may have been determined based on a fabricatedgold standard component, or based on a nominal part geometry andmaterial properties and a theoretical prediction of heat transfer forthe nominal part geometry. The master image data may include athree-dimensional or two-dimensional representation of geometry of thegold standard component or the nominal part geometry, and may alsoinclude thermal response data of the gold standard component ordetermined based on a nominal part geometry and material properties anda theoretical prediction of heat transfer for the nominal part geometry.The computing device then may compare the two-dimensional image data tothe master image data to determine any discrepancies between the morphedtwo-dimensional image data and the master image data. The computingdevice may compare any discrepancies to at least one threshold value,and, responsive to determining that a respective discrepancy is greaterthan or equal to the threshold value, the computing device may identifythe respective discrepancy. In some examples, the computing device mayoutput the morphed two-dimensional image data for display, e.g., asaligned with the geometry of the three-dimensional master component, andmay highlight the respective discrepancies. This may facilitateidentification of any discrepancies between the two-dimensional imagedata and the master image data, which may facilitate identification ofdeficiencies, such as defects, damage, blockages, or the like within thetested component.

In some examples, a single inspection station may include componentsthat allow cleaning and flowing thermography testing of a component atthe single inspection location. For example, a dry ice source may beused to introduce dry ice into the internal passages of the component tobe cleaned. The dry ice may be introduced into the internal passages insolid form, such as powder, pellets, shavings, or the like, and mayimpact any debris within the internal passages, which may cause thedebris to release from the walls of the internal passages and/or shatterinto smaller pieces and be carried out of the internal passages with thedry ice.

In some examples, the dry ice may be used as to induce the temperaturechange in the component for flowing thermography, and the flowingthermography may be performed substantially simultaneously with thecleaning In other examples, the system may include a fluid source, andthe fluid may be used to perform flowing thermography on the component.Regardless of whether the dry ice or a fluid is used for flowingthermography, performing the cleaning and flowing thermography at asingle inspection station may be more time and space efficient thanutilizing two separate stations for the cleaning and the flowingthermography testing. Further, in examples in which dry ice is used toflowing thermography, cleaning and performing flowing thermographysubstantially simultaneously may be more time efficient that performingthe procedures sequentially.

In an example, the disclosure describes a system including a fluidsource fluidically coupled to a plenum, a thermal camera, at least oneflow meter, and a computing device. In accordance with this example, thecomputing device is communicatively connected to the at least one flowmeter and the thermal camera. The computing device may be configured toreceive flow rate data from the at least one flow meter during flowtesting of a first component fluidically coupled to the plenum, receivethermographic image data captured by the thermal camera during flowingthermographic testing of a second component fluidically coupled to theplenum, and associate the flow rate data to the thermographic image datato produce quantitative flowing thermographic image data.

In another example, the disclosure describes a method that includesreceiving, by a computing device, from at least one flow meter, flowrate values relating to flow testing of a first component; receiving, bythe computing device, from a thermal camera, thermographic image datacaptured by the thermal camera during flowing thermographic testing of asecond component; and associating, by the computing device, the flowrate values with the thermographic image data to produce quantitativeflowing thermographic image data.

In an additional example, the disclosure describes a computer readablestorage medium comprising instructions that, when executed, cause atleast one processor to receive, from at least one flow meter, flow ratevalues relating to flow testing of a first component; receive, from athermal camera, thermographic image data captured by the thermal cameraduring flowing thermographic testing of a second component; andassociate, the flow rate values with the thermographic image data toproduce quantitative flowing thermographic image data.

In a further example, the disclosure describes a system including athermal camera and a computing device. In accordance with this example,the computing device is configured to receive master image datarepresentative of a geometry and thermal response of at least one of atheoretical component, a fabricated gold standard component, or anaverage of a plurality of components; receive, from the thermal camera,thermographic image data representative of a thermal response of atested component; morph the thermographic image data to substantiallyalign with the three-dimensional image data and produce morphedthermographic image data; and output a representation based on themorphed thermographic image data for display.

In another example, the disclosure describes a method includingreceiving, by a computing device, master image data representative of ageometry and thermal response of at least one of a theoreticalcomponent, a fabricated gold standard component, or an average of aplurality of components; receiving, by the computing device, from athermal camera, thermographic image data representative of a thermalresponse of a tested component; morphing, by the computing device, thethermographic image data to substantially align with thethree-dimensional image data and produce morphed thermographic imagedata; and outputting, by the computing device, a representation based onthe morphed thermographic image data for display.

In a further example, the disclosure describes a computer readablestorage medium comprising instructions that, when executed, cause atleast one processor to receive master image data representative of ageometry and thermal response of at least one of a theoreticalcomponent, a fabricated gold standard component, or an average of aplurality of components; receive, from a thermal camera, thermographicimage data representative of a thermal response of a tested component;morph the thermographic image data to substantially align with thethree-dimensional image data and produce morphed thermographic imagedata; and output a representation based on the morphed thermographicimage data for display.

In an additional example, the disclosure describes a system thatincludes a source of dry ice, a thermal camera, and a computing device.In accordance with this example, the computing device is configured tocontrol the source of dry ice to cause dry ice to be introduced into aninternal passage of a tested component. The tested component may includedebris within the internal passage, and the dry ice may remove at leastsome of the debris from the internal passage. The computing device alsomay be configured to receive, from the thermal camera, thermographicimage data representative of the thermal response of the testedcomponent, and output a representation based on the thermographic imagedata.

In another example, the disclosure describes a method that includescontrolling, by a computing device, a source of dry ice to cause dry iceto be introduced into an internal passage of a tested component. Thetested component may include debris within the internal passage, and thedry ice may remove at least some of the debris from the internalpassage. The method also may include receiving, by the computing device,from a thermal camera, thermographic image data representative of thethermal response of the tested component; and outputting, by thecomputing device, a representation based on the thermographic imagedata.

In an additional example, the disclosure describes a computer readablestorage medium including instructions that, when executed, cause atleast one processor to control a source of dry ice to cause dry ice tobe introduced into an internal passage of a tested component. The testedcomponent may include debris within the internal passage, and the dryice may remove at least some of the debris from the internal passage.The computer readable storage medium may further include instructionsthat, when executed, cause the at least one processor to receive, from athermal camera, thermographic image data representative of the thermalresponse of the tested component; and output a representation based onthe thermographic image data.

The details of one or more examples are set forth in the accompanyingdrawings and the description below. Other features, objects, andadvantages will be apparent from the description and drawings, and fromthe claims.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a conceptual block diagram illustrating an example system forperforming flowing thermography on a tested component.

FIG. 2 is a conceptual block diagram illustrating an example of acomputing device.

FIG. 3 is a flow diagram illustrating an example technique forassociating flow values measured using a fabricated gold standardcomponent with flowing thermographic image data.

FIG. 4 is a flow diagram illustrating an example technique forassociating flow values measured using the tested component with flowingthermographic image data.

FIG. 5 is a conceptual block diagram illustrating an example system forperforming flash thermography and flowing thermography on a testedcomponent and morphing two-dimensional thermographic image data tosubstantially align with master image data.

FIG. 6 is a conceptual block diagram illustrating an example of acomputing device.

FIG. 7 is a flow diagram illustrating an example technique foridentifying discrepancies between two-dimensional thermographic data andmaster image data.

FIG. 8 is a conceptual block diagram illustrating an example system forperforming both cleaning of internal passages of a component using dryice and flowing thermography inspection of the component using dry ice.

FIG. 9 is a flow diagram illustrating an example technique for cleaninga tested component using dry ice and performing flowing thermography onthe tested component using dry ice.

FIG. 10 is a conceptual block diagram illustrating another examplesystem for performing both cleaning of internal passages of a componentusing dry ice and flowing thermography inspection of the component usinga fluid.

FIG. 11 is a flow diagram illustrating another example technique forcleaning a tested component using dry ice and performing flowingthermography on the tested component using a fluid.

DETAILED DESCRIPTION

The disclosure describes various techniques for non-destructivelytesting a component using thermography. Thermography includes two types:flowing thermography and flash thermography. In flash thermography, aheat source, such as a flash lamp, is used to apply heat to the outersurface of the component. The thermal camera captures image datarepresentative of the surface temperature of the component over time,which provides the thermal response of the component to the heat source.In flowing thermography, a fluid is flowed through internal passages ofthe component, and the thermal camera captures image data representativeof the surface temperature of the component over time.

In some examples, the disclosure describes systems and techniques forproducing quantitative flowing thermographic data, rather thanqualitative flowing thermographic data. In conventional flowingthermography, data produced indicates a qualitative (e.g., relative)thermal response of different locations of the tested component (e.g.,different exit orifices for the fluid flowing through the internalpassages of the component). A trained technician, e.g., with knowledgeof the nominal geometry and material properties of the tested component,may visually analyze the flowing thermography data to determine whetherthe tested component includes any deficiencies, such as blockages,defects, or damage in the internal passages of the component. However,this may be a time-consuming process and may require the technician tohave extensive training and knowledge to accurately interpret thethermographic data.

To produce quantitative flowing thermographic data, a thermal camera maycapture image data during the flowing thermography test for each of theplurality of locations (e.g., a plurality of pixels of a sensor of thethermal camera each capturing data for a corresponding location of thetested component). A computing device may receive the image data fromthe thermal camera. At least some of the locations (e.g., pixels) maycorrespond to an exit orifice of the tested component, through which thefluid used in flowing thermography can exit the tested component.

The computing device also may receive flow rate data measured by atleast one flow meter prior to, during, or after the flowing thermographytest. The flow rate data may include a flow rate for an exit orifice.The flow rate data may be produced using a fluid pulse with known flowrate. In some examples, the flow rate data includes respective flowrates for each of a plurality of exit orifices. In some examples, theflow rate data may be produced using a fabricated gold standardcomponent (e.g., a component known to include no blocked or damagedinternal passages and to correspond to nominal part geometry). In otherexamples, the flow rate data may be produced using a plurality of flowmeters placed at respective exit orifices of the tested component.

The measured flow rate for an exit orifice may be correlated to thethermographic image data (e.g., at least one pixel) for a correspondingexit orifice (e.g., the same exit orifice or a location on the testedcomponent at a location corresponding to that on the fabricated goldstandard component) to associate flow rates with the thermographic imagedata. Based on a plurality of correlations between known flow rates andimage data at corresponding exit orifices, the computing device maydetermine a relationship between the thermographic image data and flowrates. The computing device may associate flow values with pixels fromthe thermographic image data from the tested component based on thecorrelated flow rate data to form quantitative flowing thermographyimage data. In this way, the quantitative flowing thermography imagedata may provide quantitative indicators of the flow rate throughinternal passages of the tested component, rather than only qualitative(e.g., relative) flow rates through internal passages of the testedcomponent. The quantitative indicators may be used (e.g., by thecomputing device or a trained technician) to determine whether the flowof fluid through the internal passages is within or outside apredetermined range, e.g., a design range.

In some examples, a tested component may be tested using flowingthermography, flash thermography, or both. During the thermographictesting, the thermal camera may capture infrared data in the form oftwo-dimensional thermographic image data. In accordance with theseexamples, a computing device may receive the two-dimensionalthermographic image data and may morph the two-dimensional thermographicimage data to substantially align (e.g., align or nearly align) withmaster image data. The master image data may have been determined basedon testing of a fabricated gold standard component, testing of aplurality of components and generating a theoretical average componentbased on the plurality of components, or based on a nominal partgeometry, material properties, and a theoretical prediction of fluidflow and heat transfer for the nominal part geometry. The master imagedata may include a three-dimensional or two-dimensional representationof geometry of the gold standard component, the nominal part geometry orthe average geometry of the plurality of tested components, and may alsoinclude thermal response data of the gold standard component, theplurality of tested components, or determined based on a nominal partgeometry and material properties and a theoretical prediction of heattransfer for the nominal part geometry.

The two-dimensional thermographic image data may not align with themaster image data due to, for example, deviations in the geometry of thetested component from the nominal component geometry due tomanufacturing variability, defects, damage, or the like. By morphing thetwo-dimensional thermographic image data to substantially align (e.g.,align or nearly align) with the master image data, comparison betweenthe measured thermal response and the thermal response of the fabricatedgold standard component or theoretical thermal response of a nominalcomponent may be facilitated and any deviations of the thermal responseof tested component from the master image data may be easier to detect.

The computing device then may compare the two-dimensional thermographicimage data to the master image data to determine any discrepanciesbetween the morphed two-dimensional thermographic image data and themaster image data. The computing device may perform the comparison on aper-pixel basis, or may aggregate a plurality of adjacent pixels into aset and perform the comparison on a per-set basis. The computing devicemay compare any discrepancies between the two-dimensional thermographicimage data and the master image data to at least one threshold value,and, responsive to determining that a discrepancy is greater than orequal to the threshold value, the computing device may identify therespective discrepancy. In some examples, the computing device mayoutput the morphed two-dimensional thermographic image data for display,e.g., as aligned to the geometry of the three-dimensional mastercomponent, and may highlight the respective discrepancies. This mayfacilitate identification of any discrepancies between thetwo-dimensional thermographic image data and the master image data,which may facilitate identification of deficiencies, such as defects,damage, blockages, or the like within the tested component.

In some examples, a single inspection station may include componentsthat allow cleaning and flowing thermography testing of a component atthe single inspection location. For example, a dry ice source may beused to introduce dry ice into internal passages of the component to becleaned. The dry ice may be introduced into the internal passages insolid form and may impact any debris within the internal passages of thecomponent, which may cause the debris to release from the walls of theinternal passages and/or shatter into smaller pieces and be removed fromthe internal passages with the dry ice.

In some examples, the dry ice may be used to induce the temperaturechange in the component for flowing thermography, which may be performedsubstantially simultaneously with cleaning using the dry ice. In otherexamples, the system may include a fluid source, and the fluid may beused to perform flowing thermography on the component. Regardless ofwhether the dry ice or a fluid is used for flowing thermography,performing the cleaning and flowing thermography at a single inspectionstation may be more time and space efficient than utilizing two separatestations for the cleaning and the flowing thermography testing. Further,in examples in which dry ice is used for flowing thermography, cleaningand performing flowing thermography substantially simultaneously may bemore time efficient that performing the procedures sequentially.

The various techniques described herein may be used together indifferent combinations. For example, the two-dimensional thermographicimage data morphed to substantially align the master image data mayinclude quantitative flowing thermographic image data and/or may includedata generated using flowing thermography with dry ice. As anotherexample, the quantitative flowing thermographic image data may bedetermined using thermographic data generated using dry ice. Othercombinations of the techniques described herein are also contemplated bythis disclosure and will be apparent to those of ordinary skill in theart.

FIG. 1 is a block diagram illustrating an example system 10 forperforming flowing thermography on a tested component 12. System 10includes an enclosure 14 defining an inspection station. Enclosure 14encloses a stage 16 and a thermal camera 18. Also disposed withinenclosure 14 is a plurality of flow meters 20. System 10 also includes afluid source 22, which is fluidically coupled to stage 16 (e.g., aplenum 30 defined by stage 16). A valve 24 is located between fluidsource 22 and stage 16. System 10 further includes a computing device26, which may be communicatively coupled to stage 16, thermal camera 18,the plurality of flow meters 20, and/or valve 24.

System 10 includes components that allow both flow testing and flowingthermography testing at a single inspection station. This may facilitategeneration of quantitative flowing thermography data, as describedbelow. Additionally, this may simplify and speed performing flow testingand flowing thermography testing compared to examples in which flowtesting and flowing thermography is performed at two separate anddistinct inspection stations.

Although not illustrated in FIG. 1, system 10 also may include a heatsource (e.g., heat source 110 illustrated in FIG. 5). By including aheat source, system 10 also may be configured to perform flashthermography on tested component 12. In this way, in some examples,system 10 may be configured to perform flow testing, flowingthermography testing, and flash thermography on tested component 12 at asingle inspection station.

System 10 may be used to inspect components 12 with internal passages 28through which a fluid can flow. For example, system 10 may be used toinspect components with internal cooling passages and film coolingholes, such as gas turbine engine blades or vanes. Although testedcomponent 12 is described herein as a gas turbine engine blade, it willbe appreciated that system 10 and the technique described herein may beused to perform flow testing, flowing thermography, and generatequantitative flowing thermography data for other components includinginternal passages.

In some examples, stage 16 is movable relative to thermal camera 18and/or thermal camera 18 is movable relative to stage 16. For example,stage 16 may be translatable and/or rotatable along at least one axis toposition tested component 12 relative to thermal camera 18. Similarly,thermal camera 16 may be translatable and/or rotatable along at leastone axis to position thermal camera 16 relative to tested component 12.In some examples, both stage 16 and thermal camera 18 are movable in atleast one dimension. In other examples, only stage 16 or only thermalcamera 18 is movable, and the other is substantially fixed in position.

Stage 16 may be configured to selectively position and restrain testedcomponent 12 in place relative to stage 16 during testing of testedcomponent 12. In some examples, stage 16 defines a plenum 30 forreceiving fluid from fluid source 22. Stage 16 may define at least oneaperture that is substantially aligned with at least one respectiveopening in tested component 12 when tested component 12 is positionedand restrained on stage 16. In this way, stage 16 may facilitate fluidiccommunication between tested component 12 and fluid source 22.

Thermal camera 18 includes an imaging device that produces a signalresponsive to incident thermal radiation. In some examples, thermalcamera 18 includes an infrared imaging device that detects infraredradiation. Thermal camera 18 may produce image data based on the signal,which may include data related to a plurality of pixels over time. Theimage data may be representative of a temperature of a correspondinglocation of tested component 12, e.g., a location of tested component 12from which the respective pixel sensed thermal radiation over time.Thermal camera 18 may be communicatively coupled to computing device 26,e.g., via a wired or wireless communication connection (e.g., a USBconnection, Ethernet connection, a wireless connection, or the like).Thermal camera 18 may communicate the image data to computing device 26using the communication connection.

The plurality of flow meters 20 may include devices configured to detecta flow rate of fluid at the respective flow meters 20. The flow meters20 may be configured to detect, for example, mass flow rate, volumetricflow rate, or the like. Flow meters 20 may be movable such that flowmeters 20 may be positioned at predetermined locations of testedcomponent 12. For example, flow meters 20 may be placed over or adjacentto exit orifices defined in tested component 12. Exit orifices may beapertures or orifices defined in tested component 12 and fluidicallycoupled to at least one internal passage 28 defined in tested component12, through which fluid provided from fluid source 22 flows. In thisway, flow meters 20 may be operable to detect fluid flow through arespective exit orifice. Flow meters 20 may be communicatively coupledto computing device 26 e.g., via a wired or wireless communicationconnection (e.g., a USB connection, Ethernet connection, a wirelessconnection, or the like). Flow meters 20 may communicate the flow datadetected by the respective flow meters 20 to computing device 26.

Although not illustrated in FIG. 1, a flow meter may be disposed at aposition along the fluid path from fluid source 22 to internal passages28 (e.g., along fluid line 32, within plenum 30, or the like) to measurethe flow rate of fluid entering into internal passages 28. This flowmeter may be used to measure the flow rate of fluid entering intointernal passages 28 during flow testing and/or flowing thermography.

Fluid source 22 includes a source of fluid, such as compressed air, foruse during flowing thermography measurement and/or flow measurements. Insome examples, fluid supply 22 may be configured to supply one or moreliquids or other gases in addition to or in place of air. In someexamples, fluid supply 22 is configured to supply cooled fluid tocomponent 12. In other examples, fluid supply 22 may be configured tosupply to component 12 a hot fluid and/or a room temperature fluid inaddition to or in place of a cooled fluid. As shown in FIG. 1, fluidsource 22 is fluidically coupled to plenum 30 defined by stage 16 by afluid line 32. Fluid line 32 may include a pipe, conduit, tube, or thelike. Valve 24 is controllable (e.g., by computing device 26) to openand close to control a flow rate of fluid from fluid source 22 to plenum30.

Computing device 26 may include, for example, a desktop computer, alaptop computer, a workstation, a server, a mainframe, a cloud computingsystem, or the like. Computing device 26 is configured to controloperation of system 10, including, for example, stage 16, thermal camera18, flow meters 20, and/or valve 24. Computing device may becommunicatively coupled to at least one of stage 16, thermal camera 18,flow meters 20, or valve 24 using respective communication connections.In some examples, the communication connections may include networklinks, such as Ethernet, ATM, or other network connections. Suchconnections may be wireless and/or wired connections. In other examples,the communication connections may include other types of deviceconnections, such as USB, IEEE 1394, or the like.

Computing device 26 may be configured to control operation of stage 16and/or thermal camera 18 to position tested component 12 relative tothermal camera 18. For examples, as described above, computing device 26may control stage and/or thermal camera 18 to translate and/or rotatealong at least one axis to position tested component 12 relative tothermal camera 18. Positioning tested component 12 relative to thermalcamera 18 may include positioning a predetermined surface of testedcomponent 12 to be imaged using thermal camera 18.

Computing device 26 also may be configured to control valve 24 to openand close to allow fluid to flow from fluid source 22 to plenum 30 andstop fluid flow from fluid source 22 to plenum 30. In this way,computing device 26 may cause a predetermined amount of fluid to flowover a predetermined duration to produce a predetermined flow rate offluid from fluid source 22.

In accordance with some examples of this disclosure, computing device 26may be configured to receive data from thermal camera 18 and/orrespective flow meters 20 and correlate the data to produce quantitativeflowing thermography data. In some examples, computing device 22 may beconfigured to receive flow data from the respective flow meters 20 maybe representative of a flow rate of fluid detected by the respectiveflow meters 20. During flow tests, fluid, e.g., provided by fluid source22 may flow through internal passages 28 of tested component 12. Forexample, computing device 26 may control valve 24 to open apredetermined amount for a predetermined duration to cause apredetermine amount of fluid to be released from fluid source 22. Thepredetermined amount of fluid may flow through fluid line 32 to plenum30, then through internal passages 28 and out the exit orifices definedin component 12 (e.g., with flow meters 20 removed from component 12).Flow meters 20 may detect the fluid flow passing by each respective flowmeter 20, and communicate data representative of the fluid flow tocomputing device 26. Computing device 26 may associate the flow data ofeach flow meter 20 with a respective orifice defined in tested component12 (e.g., specific location of tested component 12).

Computing device 26 also may be configured to receive thermographicimage data from thermal camera 18. The thermographic image data mayinclude data for respective pixels from a sensor of thermal camera 18.Each pixel data may include intensity and/or wavelength over time,representative of a temperature of the location from which the pixel issensing thermal radiation (e.g., a location on tested component 12). Thethermographic image data may thus represent the temperature of at leasta portion of tested component 12 over time.

In flowing thermography, fluid, e.g., provided by fluid source 22 mayflow through internal passages 28 of tested component 12. For example,computing device 26 may control valve 24 to open a predetermined amountfor a predetermined duration to cause a predetermine amount of fluid tobe released from fluid source 22 (e.g., a pulse of fluid). Thepredetermined amount of fluid may flow through fluid line 32 to plenum30, then through internal passages 28 and out the exit orifices definedin component 12 (e.g., with flow meters 20 removed from component 12).The flowing fluid may produce a transient temperature change of testedcomponent 12 from an equilibrium temperature (e.g., the temperature ofthe surrounding atmosphere). As the pulse of fluid flows throughinternal passages 28 and out through the corresponding orifices, thermalcamera 18 may capture data representative of the temperature of thesurface of tested component 12, with each individual sensor (e.g.,corresponding to a pixel) capturing data representative of thetemperature of particular location of tested component 12 over time.

Computing device 26 may be configured to receive the data representativeof the temperature of the surface of tested component 12 (thermographicimage data) and process the data to produce thermographic image datasuitable for further manipulation, such as outputting as a visualrepresentation for display at a display device or correlating with theflow data measured by the flow meters 20. For example, computing device26 may be configured to assign false color values or relative grayscalevalues to respective intensity and/or wavelength values in thethermographic image data, such that the relative intensity and/orwavelength may be perceived by a user viewing the visual representation.

In some examples, computing device 26 may determine a single valuerepresentative of the thermal response of a location of tested component12 (e.g., represented by a pixel or a set of adjacent pixels) over aduration of time. For example, the duration may be from the initialchange in temperature of the location from the equilibrium temperatureuntil the location returns to the equilibrium temperature. The singlevalue may incorporate at least one attribute of the thermal response ofthe location, including, for example, maximum temperature, minimumtemperature, rate of temperature change, time to return to equilibriumtemperature, or the like.

The thermographic image data, without more, may provide a relativeindication of the fluid flow out of respective orifices of testedcomponent 12. However, a trained technician then may need to view andinterpret the visual representation to determine whether thethermographic image data indicates that any of the flow rates out of theorifices are out-of-specification, e.g., due to blockage, damage, ordefect. This may require significant training and technician time tointerpret the thermographic imaging data, and also may leave room fortechnician error in interpreting the visual representation.

In accordance with some examples, computing device 26 may be configuredto correlate flow data received from flow meters 20 and thermographicimage data received from thermal camera 18 to associate flow values withthe thermographic image data to produce quantitative flowingthermographic image data. For example, computing device 26 may associateflow values determined for respective orifices at which a respective oneof flow meters 20 were positioned with thermographic image data valuesfor the respective orifices. By performing this correlation, computingdevice 26 may associate different flow values with differentthermographic image data values, and may determine a relationshipbetween flow values and thermographic image data values. Computingdevice 26 then may use this relationship to associate flow values withthermographic image data values for other locations of tested component12.

Hence, computing device 26 may be configured to associate quantitativeflow rate values to thermographic image data to produce quantitativeflowing thermographic image data. Quantitative flowing thermographicimage data may facilitate determination, e.g., by computing device 26 ora technician, of whether flow rates from respective orifices are withinspecification. For example, the specification may define flow ratevalues for respective orifices in response to a predefined flow intointernal passages 28. The flow rates of respective orifices from thequantitative flowing thermographic image data may be compared (e.g., bycomputing device 26 or a technician) to the respective defined flow ratevalues to determine whether the measured flow rates are withinspecification or outside of specification (e.g., due to damage, defect,blockages, or the like).

FIG. 2 is a conceptual block diagram illustrating an example ofcomputing device 26 illustrated in FIG. 1. In the example illustrated inFIG. 2, computing device 26 includes one or more processors 40, one ormore input devices 42, one or more communication units 44, one or moreoutput devices 46, and one or more storage devices 48. In some examples,one or more storage devices 48 stores thermographic image processingmodule 50 and correlation module 52. In other examples, computing device26 may include additional components or fewer components than thoseillustrated in FIG. 2.

One or more processors 40 are configured to implement functionalityand/or process instructions for execution within computing device 26.For example, processors 40 may be capable of processing instructionsstored by storage device 48. Examples of one or more processors 40 mayinclude, any one or more of a microprocessor, a controller, a digitalsignal processor (DSP), an application specific integrated circuit(ASIC), a field-programmable gate array (FPGA), or equivalent discreteor integrated logic circuitry.

One or more storage devices 48 may be configured to store informationwithin computing device 26 during operation. Storage devices 48, in someexamples, include a computer-readable storage medium orcomputer-readable storage device. In some examples, storage devices 48include a temporary memory, meaning that a primary purpose of storagedevice 48 is not long-term storage. Storage devices 48, in someexamples, include a volatile memory, meaning that storage device 48 doesnot maintain stored contents when power is not provided to storagedevice 48. Examples of volatile memories include random access memories(RAM), dynamic random access memories (DRAM), static random accessmemories (SRAM), and other forms of volatile memories known in the art.In some examples, storage devices 48 are used to store programinstructions for execution by processors 40. Storage devices 48, in someexamples, are used by software or applications running on computingdevice 26 to temporarily store information during program execution.

In some examples, storage devices 48 may further include one or morestorage device 48 configured for longer-term storage of information. Insome examples, storage devices 48 include non-volatile storage elements.Examples of such non-volatile storage elements include magnetic harddiscs, optical discs, floppy discs, flash memories, or forms ofelectrically programmable memories (EPROM) or electrically erasable andprogrammable (EEPROM) memories.

Computing device 26 further includes one or more communication units 44.Computing device 26 may utilize communication units 44 to communicatewith external devices (e.g., stage 16, thermal camera 18, flow meters20, and/or valves 24) via one or more networks, such as one or morewired or wireless networks. Communication unit 44 may be a networkinterface card, such as an Ethernet card, an optical transceiver, aradio frequency transceiver, or any other type of device that can sendand receive information. Other examples of such network interfaces mayinclude WiFi radios or Universal Serial Bus (USB). In some examples,computing device 26 utilizes communication units 44 to wirelesslycommunicate with an external device such as a server.

Computing device 26 also includes one or more input devices 42. Inputdevices 42, in some examples, are configured to receive input from auser through tactile, audio, or video sources. Examples of input devices42 include a mouse, a keyboard, a voice responsive system, video camera,microphone, touchscreen, or any other type of device for detecting acommand from a user.

Computing device 26 may further include one or more output devices 46.Output devices 46, in some examples, are configured to provide output toa user using audio or video media. For example, output devices 46 mayinclude a display, a sound card, a video graphics adapter card, or anyother type of device for converting a signal into an appropriate formunderstandable to humans or machines.

Computing device 26 also may include thermographic image processingmodule 50 and correlation module 52. Thermographic image processingmodule 50 and correlation module 52 may be implemented in various ways.For example, thermographic image processing module 50 and/or correlationmodule 52 may be implemented as an application executed by one or moreprocessors 40. In other examples, thermographic image processing module50 and/or correlation module 52 may be implemented as part of a hardwareunit of computing device 20 or as part of an operating system providedby computing device 20. Functions performed by thermographic imageprocessing module 50 and correlation module 52 are explained below withreference to the example flow diagrams illustrated in FIGS. 3 and 4.

Computing device 26 may include additional components that, for clarity,are not shown in FIG. 2. For example, computing device 26 may include apower supply to provide power to the components of computing device 26.Similarly, the components of computing device 26 shown in FIG. 2 may notbe necessary in every example of computing device 26.

In accordance with some examples of the disclosure, computing device 26can be configured to receive flow data from flow meters 20, receivethermographic image data from thermal camera 18, and generatequantitative flowing thermographic image data by associating flow valueswith thermographic image data. FIG. 3 is a flow diagram illustrating anexample technique for associating flow values measured using afabricated gold standard component with flowing thermographic imagedata. Although the technique of FIG. 3 will be described with respect tosystem 10 of FIG. 1 and computing device 26 of FIG. 2, in otherexamples, the technique of FIG. 3 may be performed using a differentsystem. Additionally, system 10 and computing device 26 may performother techniques to associate flow values with flowing thermographicimage data (e.g., the technique illustrated in FIG. 4).

The technique illustrated in FIG. 3 includes determining at least oneflow value using at least one flow meter 20 adjacent to at least onerespective exit orifice of a fabricated gold standard component (62).The fabricated gold standard component may be positioned on andrestrained with respect to stage 16, similar to tested component 12illustrated in FIG. 1. The fabricated gold standard component may be acomponent known to include no blocked or damaged internal passages andto correspond to nominal part geometry. The fabricated gold standardcomponent also may have a geometry substantially similar to testedcomponent 12 (e.g., the same aside from any damage, defects, blockages,or deviation from design specifications in tested component 12). Asdescribed above, in some examples, the component may include a gasturbine component, such as a gas turbine engine blade or vane. In someexamples, internal passages 28 may include internal cooling channels,and the exit orifices may include film cooling holes. In such examples,the fabricated gold standard component may define a geometrycorresponding to the nominal (e.g., designed) blade or vane geometry,and may include no blocked or damaged internal cooling channels and filmcooling holes.

As shown in FIG. 1, flow meters 20 may be placed adjacent to the exitorifices to measure fluid flow exiting the respective exit orifices.Although three flow meters 20 are depicted in FIG. 1, in other examples,fewer or more flow meters 20 may be used to measure flow values. Therespective flow values may represent a flow rate out of a correspondingone of the exit orifices, which may be representative of the flow ratethrough the internal passage fluidically coupled to the exit orifice.

To measure the flow values, computing device 26 (e.g., one or moreprocessors 40 executing instructions) may control valve 24 to open apredetermined amount for a predetermined duration to cause apredetermine amount of fluid to be released from fluid source 22. Thepredetermined amount of fluid may flow through fluid line 32 to plenum30, then through internal passages 28 and out the exit orifices definedin component 12 (e.g., with flow meters 20 removed from component 12).Flow meters 20 may detect the fluid flow passing by each respective flowmeter 20, and communicate data representative of the fluid flow tocomputing device 26. Computing device 26 may associate the flow data ofeach flow meter 20 with a respective exit orifice defined in thefabricated gold standard component (e.g., a specific location of thefabricated gold standard component).

The technique of FIG. 3 also includes determining whether an offset tothe flow values should be used (64). The offset may be used whenconditions specific to the day (e.g., temperature in the system 10,pressure within fluid source 22, ambient pressure, or the like) causethe flow values to be different than they would otherwise be on adifferent day (e.g., a day with a different temperature or pressure).Responsive to computing device 26 determining that an offset should beused, computing device 26 may set the offset (66) and apply the offsetto the measured flow values. Responsive to computing device 26determining that an offset should not be used, computing device 26 maynot set the offset, but may instead proceed to begin thermographicinspection of tested component 12 (68).

After flow testing of the fabricated gold standard component, thefabricated gold standard component may be removed from stage 16, andtested component 12 may be positioned and restrained on stage 16. Thetechnique of FIG. 3 then includes performing flowing thermography ontested component 12 (68). During flowing thermography, computing device26 may be configured to control valve 24 to open a predetermined amountfor a predetermined duration to cause a predetermine amount of fluid tobe released from fluid source 22 during the predetermined duration(e.g., a pulse of fluid). In some examples, the amount of fluid and flowrate entering into internal passages 28 through plenum 30 during flowingthermography may be the same as the amount of fluid and flow rateentering into internal passages 28 through plenum 30 during flow ratemeasurement.

The predetermined amount of fluid may flow through fluid line 32 toplenum 30, then through internal passages 28 and out the exit orificesdefined in component 12 (e.g., with flow meters 20 removed fromcomponent 12). The flowing fluid may produce a transient temperaturechange of tested component 12 from an equilibrium temperature (e.g., thetemperature of the surrounding atmosphere). As the pulse of fluid flowsthrough internal passages 28 and out through the corresponding orifices,thermal camera 18 may capture data representative of the temperature ofthe surface of tested component 12, with each individual sensor (e.g.,corresponding to a pixel) capturing data representative of thetemperature of particular location of tested component 12 over time.

Computing device 26 and, more particularly, thermographic imageprocessing module 50, may be configured to receive the datarepresentative of the temperature of the surface of tested component 12(thermographic image data) and process the thermographic image data toproduce a type of data suitable for further manipulation, such asoutputting as a visual representation of the thermographic image data orassociating with flow values based on the measured flow values from thefabricated gold standard component. For example, thermographic imageprocessing module 50 may be configured to assign false color values orgrayscale values to respective pixels in the thermographic image databased on the intensity and/or wavelength of the sensed by a pixel overtime, such that the relative sensed intensity and/or wavelength may beperceived by a user viewing the visual representation.

In some examples, thermographic image processing module 50 may determinea single value representative of the thermal response of a location oftested component 12 over a duration of time. In some examples,thermographic image processing module 50 may be configured to group aplurality of adjacent pixels, e.g., based on a similar thermal response,and determine a single value representative of the average thermalresponse of the group of adjacent pixels over the duration of time. Inother examples, thermographic image processing module 50 may beconfigured to, for each individual pixel, determine a single valuerepresentative of the thermal response of the respective pixel over theduration of time. In some examples, the duration may begin at theinitial change in temperature of the location from the equilibriumtemperature and end at the time the location approximately returns tothe equilibrium temperature.

The single value for the thermal response of a pixel or a group ofpixels during the duration of time may incorporate at least oneattribute of the thermal response of the location. The at least oneattribute of the thermal response of the location may include, forexample, the maximum temperature (e.g., represented by maximum detectedintensity and/or detected wavelength), minimum temperature (e.g.,represented by maximum detected intensity and/or detected wavelength),rate of temperature change (e.g., represented by rate of change indetected intensity and/or rate of change of detected wavelength), timeto return to equilibrium temperature, or the like. In some examples,thermographic image module 26 may determine the single value for thethermal response of the pixel or group of pixels based on only one ofthese attributes, while in other examples, thermographic image module 26may determine the single value for the thermal response of the pixel orgroup of pixels based on a weighted combination of at least twoattributes. Thermographic image module 26 may determine the single valuefor each pixel or each group of pixels that make up the thermographicimage data. Thermographic image processing module 50 then may assignrespective false color values or respective grayscale values to eachdetermined single value. In this way, computing device may producethermographic image data, which is suitable for further manipulation,such as outputting for display at a display device or associating withquantitative flow values.

The technique of FIG. 3 also include associating, by correlation module52, flow numbers to the thermographic image data based at least in parton flow values from the fabricated gold standard component (70). Forexample, correlation module 52 may be configured to associate flowvalues determined for respective exit orifices at which a respective oneof flow meters 20 were positioned with thermographic image data values(e.g., single values) for the respective exit orifices. By performingthis correlation, correlation module 52 may associate different flowvalues with different thermographic image data values (e.g., singlevalues), and may determine a relationship between flow values andthermographic image data values. Correlation module 52 then may use thisdetermined relationship to associate flow values with thermographicimage data values for other locations of tested component 12 (e.g.,other single values for respective pixels or groups of pixels).

In this way, computing device 26 may be configured to associatequantitative flow rate values to thermographic image data to producequantitative flowing thermographic image data. Quantitative flowingthermographic image data may facilitate determination, e.g., bycomputing device 26 or a technician, of whether flow rates fromrespective exit orifices are within specification. For example, thespecification may define flow rate values for respective exit orificesin response to a predefined flow into internal passages 28. The flowrates of respective exit orifices from the quantitative flowingthermographic image data may be compared (e.g., by computing device 26or a technician) to the respective defined flow rate values to determinewhether the measured flow rates are within specification or outside ofspecification (e.g., due to damage, defect, blockages, or the like).

In some examples, correlation module 52 may be configured to assignrespective false color values or respective grayscale values to eachflow value. Correlation module 52 then may be configured to output avisual representation based on the quantitative flowing thermographicimage data for display at a display (e.g., one or more output devices46) (72). For example, correlation module 52 may be configured to outputthe flow values as a function of position. This may allow a user tovisually perceive the quantitative flowing thermographic image data as afunction of position on tested component 12, which may facilitateanalysis of the quantitative flowing thermographic image data todetermine if flow rates at various locations of tested component 12 arewithin specification.

Although a fabricated gold standard component is used to determine flowrates in the example illustrated in FIG. 3, in other examples, afabricated gold standard component may not be utilized and flow ratesmay be determined at respective locations of tested component 12. FIG. 4is another flow diagram illustrating an example technique forassociating flow values determined using tested component 12 withflowing thermographic image data. Although the technique of FIG. 4 willbe described with respect to system 10 of FIG. 1 and computing device 26of FIG. 2, in other examples, the technique of FIG. 4 may be performedusing a different system. Additionally, system 10 and computing device26 may perform other techniques to associate flow values to flowingthermographic image data (e.g., the technique illustrated in FIG. 3).

The technique of FIG. 4 includes determining flow values using flowmeters 20 attached to tested component 12 adjacent to respective exitorifices (82). As described above, in some examples, tested component 12may include a gas turbine component, such as a gas turbine engine bladeor vane. In some examples, internal passages 28 may include internalcooling channels, and the exit orifices may include film cooling holes.

As shown in FIG. 1, flow meters 20 may be placed adjacent to the exitorifices to measure fluid flow exiting the respective exit orifices.Although three flow meters 20 are depicted in FIG. 1, in other examples,fewer or more flow meters 20 may be used to measure flow values. Therespective flow values may represent a flow rate out of a correspondingone of the exit orifices, which may be representative of the flow ratethrough the internal passage fluidically coupled to the exit orifice.

To measure the flow values, computing device 26 (e.g., one or moreprocessors 40 executing instructions) may control valve 24 to open apredetermined amount for a predetermined duration to cause apredetermine amount of fluid to be released from fluid source 22. Thepredetermined amount of fluid may flow through fluid line 32 to plenum30, then through internal passages 28 and out the exit orifices definedin component 12 (e.g., with flow meters 20 removed from component 12).Flow meters 20 may detect the fluid flow passing by each respective flowmeter 20, and communicate data representative of the fluid flow tocomputing device 26. Computing device 26 may associate the flow data ofeach flow meter 20 with a respective exit orifice defined in testedcomponent 12. After flowing the fluid through internal passages 28 anddetermining the flow values (82), flow meters 20 may be removed fromadjacent to the exit orifices, leaving the exit orifices uncovered.

The technique of FIG. 4 also includes performing flowing thermography ontested component 12 (86). This step may be similar to or substantiallythe same as step (68) described with respect to FIG. 3. The technique ofFIG. 4 then may include associating, by correlation module 52, flowvalues to the thermographic image data produced by flowing thermographybased on flow values measured using flow meters 20 (88). For example,correlation module 52 may be configured to associate flow valuesdetermined for respective exit orifices at which a respective one offlow meters 20 were positioned with thermographic image data values(e.g., single values) for the respective exit orifices. By performingthis correlation, correlation module 52 may associate different flowvalues with different thermographic image data values (e.g., singlevalues), and may determine a relationship between flow values andthermographic image data values. Correlation module 52 then may use thisdetermined relationship to associate flow values with thermographicimage data values for other locations of tested component 12 (e.g.,other single values for respective pixels or groups of pixels).

In this way, computing device 26 may be configured to associatequantitative flow rate values to thermographic image data to producequantitative flowing thermographic image data. Quantitative flowingthermographic image data may facilitate determination, e.g., bycomputing device 26 or a technician, of whether flow rates fromrespective exit orifices are within specification. For example, thespecification may define flow rate values for respective exit orificesin response to a predefined flow into internal passages 28. The flowrates of respective exit orifices from the quantitative flowingthermographic image data may be compared (e.g., by computing device 26or a technician) to the respective defined flow rate values to determinewhether the measured flow rates are within specification or outside ofspecification (e.g., due to damage, defect, blockages, or the like).

In some examples, correlation module 52 may be configured to assignrespective false color values or respective grayscale values to eachflow value. Correlation module 52 then may be configured to output avisual representation based on the quantitative flowing thermographicimage data for display at a display (e.g., one or more output devices46) (90). For example, correlation module 52 may be configured to outputthe flow values as a function of position. This may allow a user tovisually perceive the quantitative flowing thermographic image data as afunction of position on tested component 12, which may facilitateanalysis of the quantitative flowing thermographic image data todetermine if flow rates at various locations of tested component 12 arewithin specification.

As described above, in some examples, the disclosure describestechniques for morphing two-dimensional thermographic image data tosubstantially align with master image data. The thermographic image datamay be produced using flowing thermography, flash thermography, or both.A computing device may receive the two-dimensional thermographic imagedata and may morph the two-dimensional thermographic image data tosubstantially align with master image data. FIG. 5 is a conceptual blockdiagram illustrating an example system 100 for performing flashthermography and flowing thermography on a tested component and morphingtwo-dimensional thermographic image data to substantially align withmaster image data.

In some examples, system 100 may be similar to or substantially the same(e.g., the same or nearly the same) as system 10 described withreference to FIG. 1. For example, like system 10, system 100 includes anenclosure 104, a stage 106, a thermal camera 108, a fluid source 112, avalve 114, a computing device 116, and a flow line 122. These componentsmay be similar to or substantially the same as the correspondingcomponents described with respect to FIG. 1. For example, stage 106 maybe movable (e.g., translatable and/or rotatable) in at least onedimension and/or thermal camera 108 may be movable (e.g., translatableand/or rotatable) in at least one dimension to position tested component102 with respect to thermal camera 108. Similarly, stage 106 may definea plenum 120, which is fluidly connected to fluid line 122 and internalpassages 118 of component 102 when component 102 is positioned on andrestrained with respect to stage 106.

Unlike system 10 of FIG. 1, in some examples, system 100 of FIG. 5 maynot include a flow meter. However, in other examples, system 100 mayinclude at least one flow meter. Also unlike system 10, system 100 mayinclude a heat source 110. Heat source 110 may be controlled bycomputing device 106, and may be configured to generate a pulse of heatto a surface of tested component 102. In some examples, heat source 110may include a flash lamp or an infrared heat source.

In this way, in some examples, system 100 may be configured to performboth flowing thermography and flash thermography at a single testinglocation. In other examples, system 100 may include heat source 110 andmay not include fluid source 112, fluid line 122, and valve 114, suchthat system 100 is configured to perform flash thermography and notflowing thermography. In still other examples, system 100 may notinclude heat source 110 and may include fluid source 112, fluid line122, and valve 114, such that system 100 is configured to performflowing thermography and not flowing thermography.

Regardless of whether system 100 is configured to perform flashthermography, flowing thermography, or both, computing device 116 isconfigured to receive thermographic image data from thermal camera 108.As described above, thermographic image data may include data forrespective pixels from a sensor of thermal camera 108. The data for eachpixel may include intensity and/or wavelength over time, representativeof a temperature of the location from which the pixel is sensing thermalradiation (e.g., a location on tested component 102). The thermographicimage data may thus represent the temperature of at least a portion oftested component 102 over time.

In some examples, computing device 116 may determine a single valuerepresentative of the thermal response of a location of tested component102 (e.g., represented by a pixel or a set of adjacent pixels) over aduration of time. For example, the duration may be from the initialchange in temperature of the location from the equilibrium temperatureuntil the location returns to the equilibrium temperature. The singlevalue may incorporate at least one attribute of the thermal response ofthe location, including, for example, maximum temperature, minimumtemperature, rate of temperature change, time to return to equilibriumtemperature, or the like.

In some examples, the thermographic image data may be in a formatcorresponding to a two-dimensional array, as the sensor elements ofthermal camera 108 may be arranged in a two-dimensional array. However,the two-dimensional array represents thermographic image data from aportion of three-dimensional component 102, which is a three-dimensionalobject. In some examples, the thermographic image data includeconcatenated image data from a plurality of thermography tests. Forexample, a first thermography test may be performed with component 102positioned in a first orientation relative to thermal camera 108.Component 102 then may be moved relative to thermal camera 108 to orienta different surface or a different portion of a surface of component 102toward thermal camera 108. A second thermography test may be performed.This procedure may be repeated until a predetermined portion ofcomponent 102 (e.g., all exposed surfaces of component 102) have beenimaged.

In some examples, computing device 116 may be configured to combine aplurality of sets of thermographic image data into a single setrepresentative of the thermographic response of component 102. Forexample, each set of thermographic image data may be associated with aset of coordinates representative of the orientation of component 102relative to thermal camera 108. Computing device 116 may be configuredto combine the plurality of sets of thermographic image data based onthe coordinates of the respective sets of thermographic image data. Inother examples, computing device 116 may be configured to perform one ormore image recognition techniques to recognize similar features (e.g.,representative of the same exit orifice) in two sets of thermographicimage data and combine the two sets of thermographic image data based onthe similar features.

Computing device 116 also may store and/or receive master image data.The master image data may be representative of three-dimensionalgeometry and thermal response of a theoretical component, a fabricatedgold standard component, or an average geometry and thermal response ofa plurality of tested components 102. For example, a theoreticalcomponent may be defined in a CAD/CAM file as a set of coordinatescorresponding to points on the surfaces of the theoretical component. Insome examples, the theoretical component may define a nominal or designgeometry of tested component 102. That is, the theoretical component maydefine the geometry that tested component 102 was designed to possess.However, the actual geometry of tested component 102 may depart from thegeometry of the theoretical component due to manufacturing tolerances,damage, wear, defects, or the like.

The thermal response and fluid flow characteristics of the theoreticalcomponent may also be determined using modeling. For example, based onthe nominal geometry and theoretical properties of the material(s) fromwhich the theoretical component is formed (e.g., heat transfercoefficients and the like), the thermal response of the theoreticalcomponent may be predicted using computer modeling, such as finiteelement analysis. The three-dimensional master data may include datarepresentative of the geometry of the theoretical component (e.g., a setof coordinates defining surfaces of the fabricated gold standardcomponent) and the thermal response of the theoretical component. Insome examples, the thermal response of the theoretical component may betheoretically determined using the a model of the same type ofthermography used to inspect tested component 102 and/or a model of thesame parameters (e.g., temperature and flow rate of the fluid pulse forflowing thermography or intensity of radiation in flash thermography)used to inspect tested component 102.

Similarly, the fabricated gold standard component may define a geometrysubstantially the same (e.g., the same or nearly the same) as thenominal or design geometry of tested component 102. The thermal responseof the fabricated gold standard component may be determined usingflowing thermography and/or flash thermography. The three-dimensionalmaster data may include data representative of the geometry of thefabricated gold standard component (e.g., a set of coordinates definingsurfaces of the fabricated gold standard component) and the thermalresponse of the fabricated gold standard component. In some examples,the thermal response of the fabricated gold standard component may bedetermined using the same type of thermography used to inspect testedcomponent 102 and/or the same parameters (e.g., temperature and flowrate of the fluid pulse for flowing thermography or intensity ofradiation in flash thermography) used to inspect tested component 102.

In other examples, the master data may be determined based on geometricdata and thermography results from a plurality of tested components 102.For example, computing device 116 may receive geometric data from aplurality of tested components 102 and may determine an average geometryand dimensional tolerances based on the geometric data. Computing device116 also may receive flow data for the plurality of tested components102 and/or thermographic image data for the plurality of testedcomponents 102 and may determine average flow characteristics andthermographic image data for the plurality of components 102 andtolerances for the flow data and thermographic image data. Theseaverages and tolerances (geometric, flow, and/or thermographic image)then may then constitute the master image data.

Computing device 116 may be configured to morph (e.g., translate,rotate, scale, and/or stretch) the thermographic image data tosubstantially align (e.g., align or nearly align) with the master imagedata. For example, computing device 116 may be configured to morph thethermographic image data so that each location of component 102represented in the thermographic image data substantially aligns (e.g.,aligns or nearly aligns) with a respective location represented in themaster image data.

In some examples, portions of the thermographic image data may beassociated with respective sets of coordinates representative of theorientation of component 102 relative to thermal camera 108, such thatindividual geometric features of component 102 are associated with setsof coordinates (e.g., each exit orifice may be associated with arespective set of coordinates). Similarly, portions of the master imagedata may be associated with respective sets of coordinatesrepresentative of the orientation of the fabricated gold standardcomponent relative to thermal camera 108 or representative of atheoretical orientation of the theoretical component to a theoreticalthermal camera, such that individual geometric features of thefabricated gold standard component or theoretical component areassociated with sets of coordinates (e.g., each exit orifice may beassociated with a respective set of coordinates). Computing device 116may be configured to utilize the sets of coordinates for thethermographic image data and the sets of coordinates associated with themaster image data to perform a first morphing operation (e.g., includingtranslating, rotating, scaling, and/or stretching the thermographicimage data) and roughly align the thermographic image data to the masterimage data.

In some examples, computing device 106 may be configured to performmultiple, progressively more precise image morphing manipulations. Forexample, computing device 106 may be configured to first perform a roughalignment of the thermographic image data to the master image data,e.g., by aligning the thermographic image data to the gross geometry ofthe master image data. After the rough aligning of the thermographicimage data to the master image data, computing device 116 may beconfigured to perform another morphing manipulation to align thethermographic image data more closely to the geometry of the masterimage data. For example, computing device 116 may utilize imagerecognition techniques to recognize similar features in thethermographic image data and the master image data (e.g., featuresrepresenting smaller geometric features, such as exit orifices, internalgeometric features such as pedestals, or features of internal passages118) and morph the thermographic image data to substantially align thesimilar features. As another example, computing device 116 may utilizesets of coordinate associated with similar features of tested component102 and the fabricated gold standard or theoretical component and morphthe thermographic image data based on a different between positions ofcorresponding sets of coordinates.

In some examples, computing device 116 may be configured to morph thethermographic image data while substantially preserving (e.g.,preserving or nearly preserving) the thermal response information (e.g.,intensity and/or wavelength) contained in the thermographic image data.Because the thermal response information is what will be compared bycomputing device 116 to detect any discrepancies between the mastercomponent and the tested component 102, preserving the informationduring the morphing of the thermographic image data may facilitate moreaccurate comparisons.

Once computing device 116 has morphed the thermographic image data tosubstantially align the thermographic image data with the master imagedata, computing device 116 may compare the thermal response informationfrom the thermographic image data to the thermal response informationfrom the master image data. In some examples, computing device 116 maycompare the thermal response information on per-pixel basis. In otherexamples, computing device 116 may group adjacent pixels with similarthermal response information into a set and determine representativethermal response data for each set (e.g., each set of both thethermographic image data and the master image data). Computing device116 then may compare the thermal response information on a per-setbasis.

In some examples, the thermal response data for each pixel or each setmay include a single value representative of the thermal response of thelocation corresponding to the pixel or set over a duration of time, asdescribed above. In other examples, the thermal response data mayinclude a series of data representative of the sensed intensity and/orwavelength as a function of time throughout the duration of time. Ineither case, computing device 116 may compare the thermal response datafrom the thermographic image data and the thermal response data from themaster image data to identify any discrepancies between the thermaldata.

In some examples, computing device 116 may compare the identifieddiscrepancies to a threshold to determine whether the discrepanciesindicate a potential deficiency in tested component 102. Deficienciesmay include defects, damage, blockage, holes, inclusions, wear, or thelike. In some examples, a single threshold may be used for all thecomparisons, e.g., for data representative of all locations of testedcomponent 102. In other examples, computing device 116 may adaptivelydetermine the threshold for a respective comparison based on one or moreparameters. The parameters may include, for example, an amount thethermographic image data for the location was morphed to substantiallyalign with the master image data. For example, more extensive morphingmay indicate a greater likelihood that tested component 102 includes adeficiency at the location that was morphed, so computing device 116 mayset the threshold for identifying a discrepancy as a potentialdeficiency to a lower value. The parameters additionally oralternatively relate to geometry of the component, such as wallthickness at the location or material composition of the component atthe location, or may relate to testing conditions, such as thetemperature of the fluid flow through internal passages 118 or ambienttemperature within enclosure 104.

Computing device 116 may be configured to identify any discrepanciesgreater than the threshold value for each respective comparison aspotential deficiencies in tested component 102. The potentialdeficiencies may include, for example, geometric defects (e.g., an exitorifice was formed in a position different than the design position),structural defects (e.g., cracks, delamination of a coating, disbands,or the like) in tested component 102, damage to tested component 102, amaterial defect (e.g., an inclusion or hole), wear, or debris withininternal passages 118. In some examples, computing device 116 may beconfigured to both identify the presence of potential deficiencies andthe type of the respective potential deficiencies. In other examples,computing device 116 may be configured to identify the presence ofpotential deficiencies, but not identify the type of the respectivepotential deficiencies.

In some examples, computing device 116 may be configured to generate afalse color or a grayscale representation of the thermographic imagedata substantially aligned to the three-dimensional master data, withany potential deficiencies represented in the false color or grayscalerepresentation. For example, computing device 116 may be configured toassign a particular color or grayscale intensity to potentialdeficiencies. The color or grayscale intensity may correlate to thedifference between the discrepancy and the threshold value used to makethe comparison for the respective location, which may allow a user toperceive the magnitude of the discrepancy based on the color orgrayscale intensity. Computing device 116 may output the false color orgrayscale representation for display at a display device.

In some examples, computing device 116 may be configured to evaluatetested component 102 based on the identified potential deficiencies. Forexample, computing device 116 may count the number of identifiedpotential deficiencies and compare the number to a threshold number ofdeficiencies or multiple thresholds of numbers of deficiencies. Forexample, a first threshold number of deficiencies may be defined thatseparates acceptable components from marginal components and a secondthreshold number of deficiencies may be defined that separates marginalcomponents from unacceptable components. Computing device 116 may beconfigured to compare the identified potential deficiencies to thethreshold or thresholds and categorize tested component 102 based on thecomparison. In some examples, rather than performing the counting andcomparison for the entire tested component 102, computing device 116 maybe configured to divide tested component 102 into a plurality of logicalportions and perform the counting and comparison on a per-portion basis.Computing device 116 may be configured to categorize the individuallogical portions based on the counting and comparison. In some examples,computing device 116 may be configured to evaluate a size of a potentialdeficiency or a severity of a potential deficiency in addition toevaluating a number of potential deficiencies per logical portion or pertested component 102.

FIG. 6 is a conceptual block diagram illustrating an example ofcomputing device 116 illustrated in FIG. 5. In the example illustratedin FIG. 6, computing device 116 includes one or more processors 130, oneor more input devices 132, one or more communication units 134, one ormore output devices 136, and one or more storage devices 138. In someexamples, one or more storage devices 138 stores thermographic imagemodule 140, image morphing module 142, and deficiency identificationmodule 144. In other examples, computing device 116 may includeadditional components or fewer components than those illustrated in FIG.6.

One or more processors 130 are configured to implement functionalityand/or process instructions for execution within computing device 116.For example, processors 130 may be capable of processing instructionsstored by storage device 138. Examples of one or more processors 130 mayinclude any one or more of a microprocessor, a controller, a DSP, anASIC, a FPGA, or equivalent discrete or integrated logic circuitry.

One or more storage devices 138 may be configured to store informationwithin computing device 116 during operation. Storage devices 138, insome examples, include a computer-readable storage medium orcomputer-readable storage device. In some examples, storage devices 138include a temporary memory, meaning that a primary purpose of storagedevice 138 is not long-term storage. Storage devices 138, in someexamples, include a volatile memory, meaning that storage device 138does not maintain stored contents when power is not provided to storagedevice 138. In some examples, storage devices 138 may further includeone or more storage device 138 configured for longer-term storage ofinformation. In some examples, storage devices 138 include non-volatilestorage elements.

Computing device 116 further includes one or more communication units134. Computing device 116 may utilize communication units 134 tocommunicate with external devices (e.g., stage 106, thermal camera 108,heat source 110, and/or valves 114) via one or more networks, such asone or more wired or wireless networks. Computing device 16 alsoincludes one or more input devices 132. Input devices 132, in someexamples, are configured to receive input from a user through tactile,audio, or video sources. Examples of input devices 132 include a mouse,a keyboard, a voice responsive system, video camera, microphone,touchscreen, or any other type of device for detecting a command from auser.

Computing device 116 may further include one or more output devices 136.Output devices 136, in some examples, are configured to provide outputto a user using audio or video media. For example, output devices 136may include a display, a sound card, a video graphics adapter card, orany other type of device for converting a signal into an appropriateform understandable to humans or machines.

Computing device 136 also may include thermographic image processingmodule 140, image morphing module 142, and deficiency identificationmodule 144. Thermographic image processing module 140, image morphingmodule 142, and deficiency identification module 144 may be implementedin various ways. For example, thermographic image processing module 140,image morphing module 142, and/or deficiency identification module 144may be implemented as an application executed by one or more processors40. In other examples, thermographic image processing module 140, imagemorphing module 142, and/or deficiency identification module 144 may beimplemented as part of a hardware unit of computing device 20 or as partof an operating system provided by computing device 20. Functionsperformed by thermographic image processing module 140, image morphingmodule 142, and deficiency identification module 144 are explained belowwith reference to the example flow diagrams illustrated in FIG. 7.

Computing device 116 may include additional components that, forclarity, are not shown in FIG. 6. For example, computing device 116 mayinclude a power supply to provide power to the components of computingdevice 116. Similarly, the components of computing device 116 shown inFIG. 6 may not be necessary in every example of computing device 116.

In accordance with some examples of the disclosure, computing device 116(e.g., image morphing module 142) may be configured to morphthermographic image data to substantially align with master image data.In some examples, deficiency identification module 114 may be configuredto compare the morphed thermographic image data to the master image datato identify discrepancies between the morphed thermographic image dataand the master image data. In some examples, deficiency identificationmodule 144 may be configured to identify potential deficiencies intested component 102 based on the discrepancies between the morphedthermographic image data and the master image data. FIG. 7 is a flowdiagram illustrating an example technique for associating flow valuesmeasured using a fabricated gold standard component with flowingthermographic image data. Although the technique of FIG. 7 will bedescribed with respect to system 100 of FIG. 4 and computing device 116of FIG. 5, in other examples, the technique of FIG. 7 may be performedusing a different system. Additionally, system 100 and computing device116 may perform other techniques to morph thermographic image data tosubstantially align with master image data and identify potentialdeficiencies based on a comparison of the morphed thermographic imagedata and the master image data.

The technique of FIG. 7 includes performing thermographic inspection oftested component 102 to generate thermographic image data (152). Asdescribed above either or both of flowing thermography or flashthermography may be used to generate the thermographic image data. Inflash thermography, computing device 116 (e.g., one or more processors130) control heat source 110 to apply heat (e.g., a pulse of infraredradiation) to the outer surface of tested component 102. Thermal camera108 captures image data representative of the surface temperature oftested component 102 over time, which provides the thermal response oftested component 102 to the heat provided by heat source 110. Computingdevice 116 (e.g., thermographic image processing module 140) thenreceived the thermographic image data from thermal camera 108. Inflowing thermography, computing device 116 (e.g., one or more processors130) controls flow valve to open a predetermined amount for apredetermined time to allow a predetermined pulse of fluid to flow fromfluid source 112 to plenum 120 and through internal passages 118 oftested component 102. Thermal camera 108 captures image datarepresentative of the surface temperature of tested component 102 overtime in response to the pulse of fluid. Computing device 116 (e.g.,thermographic image processing module 140) then received thethermographic image data from thermal camera 108. As described above,the thermographic image data may include data for respective pixels froma sensor of thermal camera 108. The data for each pixel may includeintensity and/or wavelength over time, representative of a temperatureof the location from which the pixel is sensing thermal radiation (e.g.,a location on tested component 102).

In some examples, thermographic image processing module 140 may processthe thermographic image data received from thermal camera 108. Forexample, thermographic image processing module 140 may be configured todetermine a single value representative of the thermal response of alocation of tested component 102 (e.g., represented by a pixel or a setof adjacent pixels) over a duration of time. For example, the durationmay be from the initial change in temperature of the location from theequilibrium temperature until the location returns to the equilibriumtemperature. The single value may incorporate at least one attribute ofthe thermal response of the location, including, for example, maximumtemperature, minimum temperature, rate of temperature change, time toreturn to equilibrium temperature, or the like.

In some examples, thermographic image processing module 140 may beconfigured to combine thermographic image data from a plurality ofthermography tests. For example, each thermographic test may result inthermographic image data for a portion of tested component 102 (e.g., aportion at which thermal camera 108 is directed). A plurality ofthermographic tests may be utilized to collect thermographic image datafor the entire surface area of tested component 102. thermographic imageprocessing module 140 may be configured to combine a plurality of setsof thermographic image data into a single set of thermographic imagedata representative of the thermal response of a predetermined portionof component 102 (e.g., substantially all exposed surfaces of testedcomponent 102). For example, each set of thermographic image data may beassociated with a set of coordinates representative of the orientationof tested component 102 relative to thermal camera 108. Thermographicimage processing module 140 may be configured to combine the pluralityof sets of thermographic image data based on the coordinates of therespective sets of thermographic image data. In other examples,thermographic image processing module 140 may be configured to performone or more image recognition techniques to recognize similar features(e.g., representative of the same exit orifice) in two sets ofthermographic image data and combine the two sets of thermographic imagedata based on the similar features.

The technique of FIG. 7 also includes morphing the thermographic imagedata to roughly align with master image data (154). In some examples,computing device 116 includes an image morphing module 142. Imagemorphing module 142 may be configured to receive the thermographic imagedata from thermographic image processing module 140. Image morphingmodule 142 also may be configured to receive master image data.

The master image data may be representative of three-dimensionalgeometry and thermal response of a theoretical component, a fabricatedgold standard component, or an average geometry and thermal response ofa plurality of tested components 102, as described above. In someexamples, the three-dimensional geometry of the master image data may berepresentative of the geometry that tested component 102 was designed topossess. However, the actual geometry of tested component 102 may departfrom the geometry of the master image data due to manufacturingtolerances, damage to component 102, wear of component 102 during use,defects in tested component 102, or the like.

Image morphing module 142 may be configured to morph (e.g., translate,rotate, scale, and/or stretch) the thermographic image data to roughlyalign with the master image data (154). As used herein, “roughly align”means that the morphed two-dimensional thermographic image datagenerally aligns to the master image data based on general or roughgeometry of the master image data, while relatively more precisegeometrical features may remain not substantially aligned.

For example, image morphing module 142 may be configured to overlaythermographic image data on the geometry defined by the master imagedata, e.g., based on the approximate surface geometry defined by themaster image data and the approximate surface geometry represented inthe thermographic image data. As another example, image morphing module142 may be configured to roughly align the thermographic image data andthe master image data based on sets of coordinates representative of theorientation of tested component 102 relative to thermal camera 108 andsets of coordinates representative of the orientation (real ortheoretical) of the three-dimensional image data relative to thermalcamera 108. As described above, in some examples, the thermographicimage data may include sets of coordinates associated with respectivefeatures of the image data, such that individual geometric features ofcomponent 102 are associated with sets of coordinates (e.g., each exitorifice may be associated with a respective set of coordinates). In someexamples, tested component 102 may include one or more features that isincluded in tested component 102 to facilitate identification of therelative orientation of tested component 102 to thermal camera 108. Inother examples, image morphing module 142 may utilize geometric featuressuch as exit orifices (e.g., film cooling holes, a feature at aperimeter of tested component 102) to identify the orientation of testedcomponent relative to thermal camera 108. Alternatively or additionally,the location of tested component relative to stage 106 may besubstantially fixed (e.g., fixed or nearly fixed) and substantiallyconsistent (e.g., consistent or nearly consistent), and thethermographic image data may be associated with coordinates representingthe position of stage 106 relative to thermal camera 108.

Similarly, portions of the master image data may be associated withrespective sets of coordinates representative of the real or theoreticalorientation of the master image data relative to thermal camera 108,such that individual geometric features of the fabricated gold standardcomponent or theoretical component are associated with sets ofcoordinates (e.g., each exit orifice may be associated with a respectiveset of coordinates). Alternatively or additionally, when the masterimage data is based on a fabricated gold standard component or anaverage of results from a plurality of tested components 102, thelocation of the fabricated gold standard component or the averagegeometry of the plurality of tested components 102 relative to stage 106may be substantially fixed (e.g., fixed or nearly fixed) andsubstantially consistent (e.g., consistent or nearly consistent), andthe master image data may be associated with coordinates representingthe position of stage 106 relative to thermal camera 108.

Regardless of how the sets of coordinates for the thermographic imagedata and the master image data are defined, image morphing module 142may be configured to utilize the sets of coordinates for thethermographic image data and the sets of coordinates associated with themaster image data to perform a first morphing operation (e.g., includingtranslating, rotating, scaling, and/or stretching the thermographicimage data) and roughly align the thermographic image data to the masterimage data (154).

Image morphing module 142 may be configured to morph the thermographicimage data while substantially preserving (e.g., preserving or nearlypreserving) the thermal response information (e.g., intensity and/orwavelength) contained in the thermographic image data. In other words,image morphing module 142 may morph the geometric information containedin thermographic image data (e.g., by applying one or more offsets to avalue or set representative of pixel location to shift the relativepixel location while substantially preserving the thermal responseinformation associated with the pixel. Because the thermal responseinformation is what will be compared by computing device 116 to detectany discrepancies between the master component and the tested component102, preserving the thermal response information during the morphing ofthe thermographic image data may facilitate more accurate comparisonsbetween the thermographic image data and the master image data.

Once the image morphing module 142 has roughly aligned the thermographicimage data to the master image data (154), image morphing module 142 mayfurther morph the thermographic image data to substantially align withthe master image data (156). For example, image morphing module 142 mayutilize image recognition techniques to recognize similar features inthe thermographic image data and the master image data (e.g., featuresrepresenting smaller geometric features, such as exit orifices, internalgeometric features such as pedestals, or features of internal passages118) and morph the thermographic image data to substantially align thesimilar features. In some examples, during the further morphing step,image morphing module 142 may use image recognition techniques torecognize more precise (e.g., smaller) features in the thermographicimage data and/or the master image data and may utilize the more precisefeatures to achieve better alignment between the thermographic imagedata and the master image data. Examples of more precise features thatimage morphing module 142 may recognize include cooling circuit geometry(e.g., geometry of internal passages 118), internal pedestals (e.g.,pedestals of a gas turbine engine blade to which a sheet that definesthe external surface of the gas turbine engine blade is attached), exitorifices (e.g., film cooling holes of a gas turbine engine blade), orthe like. Like when image morphing module 142 is morphing thethermographic image data to roughly align with the master image data,image morphing module 142 may morph the geometric component of thethermographic image data while substantially preserving the thermalresponse data for the thermographic image data.

In some examples, image morphing module 142 may iteratively morph (e.g.,translate, rotate, stretch, and/or scale) the thermographic image datauntil the thermographic image data substantially aligns with (e.g.,aligns with or nearly aligns with) the master image data. In someexamples, image morphing module 142 may determine when the thermographicimage data is substantially aligned with the master image data based ona determine of whether at least one geometric feature (e.g., a pluralityof features) of the thermographic image data is substantially alignedwith the corresponding at least one geometric feature of the masterimage data. For example, image morphing module 142 may determine, foreach geometric feature of the plurality of geometric features, whetherthe thermographic image data substantially aligns with the master imagedata. Image morphing module 142 may then determine whether the number offeatures that substantially align (e.g., align or nearly align) aregreater than a threshold number of features. Responsive to determiningthat the number of features that substantially align is greater than thethreshold number of features, image morphing module 142 may determinethat the thermographic image data is substantially aligned with themaster image data. However, responsive to determining that the number offeatures that substantially align is less than the threshold number offeatures, image morphing module 142 may determine that the thermographicimage data is not substantially aligned with the master image data, andmay perform additional image morphing steps.

Once image morphing module 142 determines that the thermographic imagedata is substantially aligned with the master image data, deficiencyidentification module 144 may compare the thermal response data from thethermographic image data to thermal response data from the master imagedata (158). In some examples, deficiency identification module 144 maycompare the thermal response information on per-pixel basis. That is,for each pixel of the thermographic image data, deficiencyidentification module 144 may compare the thermal response data from thethermographic image data to the thermal response data for thecorresponding pixel of the master image data.

In other examples, for both the thermographic image data and the masterimage data, deficiency identification module 144 may group adjacentpixels with similar thermal response information into a set anddetermine representative thermal response data for each set. Computingdevice 116 then may compare the thermal response information on aper-set basis. That is, for each set of the thermographic image data,deficiency identification module 144 may compare the thermal responsedata from the thermographic image data to the thermal response data forthe corresponding set of the master image data.

As described above, in some examples, the thermal response data for eachpixel or each set may include a single value representative of thethermal response of the location corresponding to the pixel or set overa duration of time. In other examples, the thermal response data mayinclude a series of data representative of the sensed intensity and/orwavelength as a function of time throughout the duration of time. Ineither case, deficiency identification module 144 may compare thethermal response data from the thermographic image data and the thermalresponse data from the master image data to identify any discrepanciesbetween the thermal response data from the thermographic image data andthe thermal response data from the master image data.

Deficiency identification module 144 then may compare each identifieddiscrepancy to a respective threshold value to determine whether therespective identified discrepancy indicates a potential deficiency intested component 102 (160). In some examples, the threshold value foreach identified discrepancy may be the same. In other examples, at leastone threshold values may be different than another threshold value. Thethreshold value(s) may be determined based at least in part on one ormore parameters associated with the thermographic image data and/or themaster image data. Example parameters may include an amount thethermographic image data for the location corresponding to the locationof the respective potential deficiency was morphed; a parameter relatingto the geometry of tested component 102 at the location of therespective potential deficiency, such as wall thickness; a materialproperty of tested component 102 at the location; and/or testingconditions, such as the temperature of the fluid flow through internalpassages 118 or ambient temperature within enclosure 104.

For example, more extensive morphing of the thermographic image datacorresponding to the identified discrepancy may indicate a greaterlikelihood that tested component 102 includes a deficiency at thelocation that was morphed, so deficiency identification module 144 mayset the threshold for identifying a discrepancy as a potentialdeficiency to a lower value. Conversely, less morphing of thethermographic image data corresponding to the identified discrepancy mayindicate a lower likelihood that tested component 102 includes adeficiency at the location that was morphed, so deficiencyidentification module 144 may set the threshold for identifying adiscrepancy as a potential deficiency to a higher value.

Deficiency identification module 144 may compare each identifieddiscrepancy to the respective threshold value to determine whether therespective identified discrepancy indicates a potential deficiency intested component 102 (160). Deficiency identification module 144 may beconfigured to identify any discrepancies greater than the respectivethreshold value as potential deficiencies within tested component 102.The potential deficiencies may include, for example, geometric defects(e.g., an exit orifice was formed in a position different than thedesign position), structural defects (e.g., cracks, delamination of acoating, disbands, or the like) in tested component 102, damage totested component 102, a material defect (e.g., an inclusion or hole),wear, or debris within internal passages 118. Each of these deficienciesmay affect fluid flow within internal passages 118 and/or heat transferwithin tested component 102.

Deficiency identification module 144 then may output a representation ofthe identified potential deficiencies (162). For example, deficiencyidentification module 144 may be configured to generate a false color ora grayscale representation of the thermographic image data substantiallyaligned to the three-dimensional master data, with any identifiedpotential deficiencies represented in the false color or grayscalerepresentation. For example, deficiency identification module 144 may beconfigured to assign a particular color or grayscale intensity topotential deficiencies. The color or grayscale intensity may correlateto the difference between the discrepancy and the threshold value usedto make the comparison for the respective location, which may allow auser to perceive the magnitude of the discrepancy based on the color orgrayscale intensity. Deficiency identification module 144 may output thefalse color or grayscale representation for display at a display deviceincluded in or coupled to computing device 116 (e.g., one of outputdevices 136).

As another example, deficiency identification module 144 may beconfigured to count the number of identified potential deficiencies andcompare the number to at least one threshold number of deficiencies. Forexample, deficiency identification module 144 may compare the number ofidentified potential deficiencies to a threshold number of deficienciesand determine whether tested component 102 is acceptable or notacceptable based on the comparison. Responsive to determining that thenumber of identified potential deficiencies is greater than thethreshold number of deficiencies, deficiency identification module 144may determine that tested component 102 is unacceptable. Responsive todetermining that the number of identified potential deficiencies is lessthan the threshold number of deficiencies, deficiency identificationmodule 144 may determine that the tested component 102 is acceptable.

As another example, deficiency identification module 144 may compare thenumber of identified potential deficiencies to a first threshold numberof deficiencies to determine whether the tested component 102 isacceptable. Responsive to determining that the number of identifiedpotential deficiencies is less than the first threshold number ofdeficiencies, deficiency identification module 144 may determine thatthe tested component 102 is acceptable. Responsive to determining thatthe number of identified potential deficiencies is less than thethreshold number of deficiencies, deficiency identification module 144may compare the number of identified potential deficiencies to a secondthreshold number of deficiencies. The second threshold number ofdeficiencies may be selected to discriminate between marginal componentsand unacceptable components. Responsive to determining that the numberof identified potential deficiencies is greater than the secondthreshold number of deficiencies, deficiency identification module 144may determine that tested component 102 is unacceptable. Responsive todetermining that the number of identified potential deficiencies is lessthan the second threshold number of deficiencies, deficiencyidentification module 144 may determine that the tested component 102 ismarginal. In some examples, deficiency identification module 144 may beconfigured to output an indication of the categorization of testedcomponent 102, and, in some examples, further information regarding thenumber and/or location of the identified potential deficiencies.

In some examples, rather than performing the counting and comparisons ona per-component basis, deficiency identification module 144 may beconfigured to logically divide tested component 102 (e.g., thethermographic image data representative of tested component 102) into aplurality of portions. Deficiency identification module 144 then maycount identified potential deficiencies on a per-portion basis, and, foreach portion, compare the number of identified potential deficiencies toat least one threshold number of deficiencies. In some examples,deficiency identification module 144 may be configured to output anindication of the categorization of each portion of tested component102, and, in some examples, further information regarding the numberand/or location of the identified potential deficiencies in each portionof tested component 102.

In some examples, computing device 116 may be configured to evaluate asize of a potential deficiency or a severity of a potential deficiency(e.g., based at least in part on the magnitude of the discrepancybetween the master image data and the thermographic image data) inaddition to evaluating a number of potential deficiencies per logicalportion or per tested component 102.

In this way, morphing the thermographic image data to substantiallyalign with master image data and comparing the morphed thermographicimage data to the master image data may facilitate identificationpotential deficiencies in tested component 102. In some examples, themorphing procedure and the comparison between the thermographic imagedata and the master image data may be automated (e.g., carried out bycomputing device 116 automatically with little or no under interventionafter initiating the technique). In some examples, computing device 116may output a representation of the identified potential deficiencies,which a trained technician may view and use to determine whether testedcomponent 102 is acceptable or unacceptable. In some examples, computingdevice 116 may automatically make a determination of whether testedcomponent is acceptable or unacceptable (and, optionally, marginal)based on the number and/or severity of the identified potentialdeficiencies.

In some examples, as described above, a single inspection station mayinclude components that allow both cleaning of internal passages of thecomponent using dry ice and flowing thermography inspection of thecomponent. FIG. 8 is a conceptual block diagram illustrating an examplesystem 170 for performing both cleaning of internal passages of acomponent 172 using dry ice and flowing thermography inspection of thecomponent 172. Performing the cleaning using dry ice and flowingthermography at a single inspection station may be more time and spaceefficient than utilizing two separate stations for the cleaning and theflowing thermography testing. Further, in examples in which dry ice isused to flowing thermography, cleaning and performing flowingthermography substantially simultaneously may be more time efficientthat performing the procedures sequentially.

System 170 may be similar to or substantially the same (e.g., the sameor nearly the same) as system 10 described with reference to FIG. 1. Forexample, like system 10, system 100 includes an enclosure 174 definingan inspection station, a stage 176 defining a plenum 180, a thermalcamera 178, a valve 184, a computing device 186, and a flow line 184.These components may be similar to or substantially the same as thecorresponding components described with respect to FIG. 1. For example,stage 176 may be movable (e.g., translatable and/or rotatable) in atleast one dimension and/or thermal camera 178 may be movable (e.g.,translatable and/or rotatable) in at least one dimension to positiontested component 172 with respect to thermal camera 178.

Although not illustrated in FIG. 8, system 170 also may include a heatsource (e.g., heat source 110 illustrated in FIG. 5). By including aheat source, system 170 also may be configured to perform flashthermography on tested component 172. In this way, in some examples,system 170 may be configured to perform cleaning using dry ice, flowingthermography testing, and flash thermography on tested component 172 ata single inspection station.

Unlike system 10 of FIG. 1, system 170 includes a dry ice source 182.Dry ice source 182 may be fluidically coupled to plenum 180 by flow line184. Computing device 186 may be configured to control dry ice source182 to control introduction of dry ice into plenum 180, and, ultimately,internal passages 188 of tested component 172.

FIG. 8 also illustrates exit orifices 190A, 190B, and 190C(collectively, “exit orifices 190”) defined in tested component 172.First exit orifice 190A is fluidically coupled to first internal passage188A and defines the exit point from fluid flowing through internalpassage 188A. Similarly, second exit orifice 190B is fluidically coupledto second internal passage 188B, and third exit orifice 190C isfluidically coupled to second internal passage 188C. In some examples,internal passages 188 may include internal cooling channels, and exitorifices 190 may include film cooling holes.

FIG. 9 is a flow diagram illustrating an example technique that may beimplemented by system 170 (e.g., under control of computing device 186)to clean tested component 172 and perform flowing thermography on testedcomponent 172 using dry ice. Although the technique of FIG. 9 will bedescribed with respect to system 170 of FIG. 8, in other examples, thetechnique of FIG. 9 may be performed using a different system.Additionally, system 170 may perform other techniques to clean testedcomponent 172 and perform flowing thermography on tested component 172.

The technique illustrated in FIG. 9 includes introducing dry ice intointernal passages 188 of tested component 172 (202). Computing device186 may be configured to control dry ice source 182 to controlintroduction of dry ice into plenum 180, and, ultimately, internalpassages 188 of tested component 172.

The dry ice may be in solid form, such as powder, pellets, shavings, orthe like, and may impact any debris within internal passages 188. Thedebris may be present within internal passages 188 due to ingestion ofdust, dirt, or other particulates during use of tested component 172,e.g., as a blade of a gas turbine engine. Alternatively or additionally,the debris may have been formed during manufacture of tested component172, e.g., may be a portion of a casting used to define internalpassages 188 during formation of tested component 172. The introductionof dry ice into internal passages 188 may cause the debris to releasefrom the walls of the internal passages and/or shatter into smallerpieces and be carried out of internal passages 188 through exit orifices190 with the dry ice. In some examples, at least a portion of the dryice may sublimate to vapor within internal passages 188. Exiting ofgaseous dry ice from a respective one of exit orifices 190 may be usedto confirm clear flow within the respective exit orifice 190. In thisway, the dry ice may be used to clean internal passages 188 of debris.

The introduction of dry ice into internal passages 188 may produce atransient temperature change of tested component 172 from an equilibriumtemperature (e.g., the temperature of the surrounding atmosphere). Thetechnique of FIG. 9 also includes detecting the thermal response oftested component 172 using thermal camera 178 (204). As the dry ice isintroduced into and travels through internal passages 188 and outthrough the corresponding exit orifices 190, thermal camera 178 maycapture data representative of the temperature of the surface of testedcomponent 172, with each individual sensor (e.g., corresponding to apixel) of thermal camera 178 capturing data representative of thetemperature of particular location of tested component 172 over time.The thermographic image data may include, for example, the wavelengthand/or intensity of radiation detected by each individual sensor as afunction of time. Computing device 186 may be configured to receive thethermographic image data from thermal camera 178.

The technique of FIG. 9 further includes outputting a representationbased on the thermal response of tested component 172 (206). In someexamples, computing device 186 may process the thermographic image datareceived from thermal camera 178. For example, computing device 186 maybe configured to determine a single value representative of the thermalresponse of a location of tested component 172 (e.g., represented by apixel or a set of adjacent pixels) over a duration of time. For example,the duration may be from the initial change in temperature of thelocation from the equilibrium temperature until the location returns tothe equilibrium temperature. The single value may incorporate at leastone attribute of the thermal response of the location, including, forexample, maximum temperature, minimum temperature, rate of temperaturechange, time to return to equilibrium temperature, or the like.

In some examples, computing device 186 may be configured to combinethermographic image data from a plurality of thermography tests. Forexample, each thermographic test may result in thermographic image datafor a portion of tested component 172 (e.g., a portion at which thermalcamera 178 is directed). A plurality of thermographic tests may beutilized to collect thermographic image data for the entire surface areaof tested component 172. Computing device 186 may be configured tocombine a plurality of sets of thermographic image data into a singleset of thermographic image data representative of the thermal responseof a predetermined portion of tested component 172 (e.g., substantiallyall exposed surfaces of tested component 172). For example, each set ofthermographic image data may be associated with a set of coordinatesrepresentative of the orientation of tested component 172 relative tothermal camera 178. Computing device 186 may be configured to combinethe plurality of sets of thermographic image data based on thecoordinates of the respective sets of thermographic image data. In otherexamples, computing device 186 may be configured to perform one or moreimage recognition techniques to recognize similar features (e.g.,representative of the same exit orifice) in two sets of thermographicimage data and combine the two sets of thermographic image data based onthe similar features.

In some examples, outputting a representation based on the thermalresponse of tested component 172 (206) may include outputting a falsecolor or a grayscale representation of the thermographic image data. Forexample, computing device 186 may be configured to associate respectivesingle values with corresponding false color values or correspondinggrayscale values. Computing device 186 may then output the false coloror grayscale representation for display at a display device included inor operatively coupled to computing device 186.

As another example, computing device 186 may be configured to morph thethermographic image data to substantially align with three-dimensionalmaster data as described above with respect to FIGS. 5-7, and computingdevice 186 may be configured to compare the thermographic image data tothe three-dimensional master data to identify any potentialdeficiencies. Computing device 186 may be configured to assign aparticular color or grayscale intensity to potential deficiencies. Thecolor or grayscale intensity may correlate to the difference between thediscrepancy and the threshold value used to make the comparison for therespective location, which may allow a user to perceive the magnitude ofthe discrepancy based on the color or grayscale intensity. Computingdevice 186 may output the false color or grayscale representation fordisplay at a display device included in or coupled to computing device186.

As another example, computing device 186 may be configured to receivethe thermographic image data and flow rate data measured by at least oneflow meter during, prior to, or after the flowing thermography test, asdescribed above with respect to FIGS. 1-4. Computing device 186 mayassociate flow values with the thermographic image data based on theflow rate data to generate quantitative flowing thermography image data.Computing device 186 may be configured to assign a particular color orgrayscale intensity to respective flow values. Computing device 186 mayoutput the false color or grayscale representation for display at adisplay device included in or coupled to computing device 186.

While FIGS. 8 and 9 illustrate a system and describe a technique forsubstantially simultaneously (e.g., simultaneously or nearlysimultaneously) cleaning component 172 and performing flowingthermography testing of component 172 using dry ice, in other examples,a system may be configured to clean a component using dry ice and thenperform flowing thermography testing of the component using a fluidsource. FIG. 10 is a conceptual diagram illustrating an example system210 cleaning a tested component 212 using dry ice and performing flowingthermography on the tested component 212 using a fluid. Performing thecleaning using dry ice and flowing thermography at a single inspectionstation may be more time and space efficient than utilizing two separatestations for the cleaning and the flowing thermography testing.

System 210 may be similar to or substantially the same (e.g., the sameor nearly the same) as system 170 described with reference to FIG. 8.For example, like system 170, system 210 includes an enclosure 214defining an inspection station, a stage 216 defining a plenum 220, athermal camera 218, and a computing device 186. These components may besimilar to or substantially the same as the corresponding componentsdescribed with respect to FIG. 8. For example, stage 216 may be movable(e.g., translatable and/or rotatable) in at least one dimension and/orthermal camera 218 may be movable (e.g., translatable and/or rotatable)in at least one dimension to position tested component 212 with respectto thermal camera 218.

Although not illustrated in FIG. 10, system 210 also may include a heatsource (e.g., heat source 110 illustrated in FIG. 5). By including aheat source, system 210 also may be configured to perform flashthermography on tested component 212. In this way, in some examples,system 210 may be configured to perform cleaning using dry ice, flowingthermography testing, and flash thermography on tested component 212 ata single inspection station.

Unlike system 170 of FIG. 8, system 210 includes a dry ice source 222and a fluid source 234. Dry ice source 222 includes a source of dry ice(e.g., solid dry ice in the form of pellets, powder, shavings, or thelike). Dry ice source 222 may be fluidically coupled to plenum 220 byflow line 232. Computing device 226 may be configured to control dry icesource 222 to control introduction of dry ice into plenum 220, and,ultimately, internal passages 228 of tested component 212.

Fluid source 234 includes a source of fluid, such as compressed air, foruse during flowing thermography measurement and/or flow measurements. Insome examples, fluid source 234 may be configured to supply one or moreliquids or other gases in addition to or in place of air. In someexamples, fluid source 234 is configured to supply cooled fluid totested component 212. In other examples, fluid source 234 may beconfigured to supply to component 212 a hot fluid and/or a roomtemperature fluid in addition to or in place of a cooled fluid. As shownin FIG. 10, fluid source 234 is fluidically coupled to plenum 220 by afluid line 238. Valve 236 is controllable (e.g., by computing device226) to open and close valve 236 to control a flow rate of fluid fromfluid source 234 to plenum 220.

FIG. 11 is a flow diagram illustrating an example technique that may beimplemented by system 210 (e.g., under control of computing device 226)to clean tested component 212 using dry ice and perform flowingthermography on tested component 212 using a fluid. Although thetechnique of FIG. 11 will be described with respect to system 210 ofFIG. 10, in other examples, the technique of FIG. 11 may be performedusing a different system. Additionally, system 210 may perform othertechniques to clean tested component 212 and perform flowingthermography on tested component 212.

The technique illustrated in FIG. 11 includes cleaning internal passages228 of tested component 212 by introducing dry ice into internalpassages 228 of tested component 212 (242). Computing device 226 may beconfigured to control dry ice source 222 to control introduction of dryice into plenum 220, and, ultimately, internal passages 228 of testedcomponent 212.

The dry ice may be in solid form, such as powder, pellets, shavings, orthe like, and may impact any debris within internal passages 188. Insome examples, contact with the dry ice may release at least some of thedebris from the walls of internal passages 228 and the dry ice mayremove the debris out of internal passages 228 through respective onesof exit orifices 230. In this way, the dry ice may be used to cleaninternal passages 228 of debris.

The technique of FIG. 11 also includes flowing the fluid throughinternal passages 228 of tested component 212 (244). To flow gaseous dryice through internal passages 228, computing device 226 may beconfigured to control valve 236 to open a predetermined amount for apredetermined duration to cause a predetermined amount of the fluid tobe released from fluid source 222 during the predetermined duration(e.g., a pulse of fluid). The pulse of fluid may flow through fluid line238 to plenum 220, then through internal passages 228 and out exitorifices 230 defined in tested component 212.

The pulse of fluid may produce a transient temperature change in testedcomponent 212 from an equilibrium temperature (e.g., the temperature ofthe surrounding atmosphere). In some examples, the fluid may be at atemperature lower, substantially the same as, or higher than theequilibrium temperature of tested component 212. The technique of FIG.11 also includes detecting the thermal response of tested component 212using thermal camera 218 (246). As the pulse of fluid flows throughinternal passages 228 and out through the corresponding exit orifices230, thermal camera 218 may capture data representative of thetemperature of the surface of tested component 212, with each individualsensor (e.g., corresponding to a pixel) of thermal camera 218 capturingdata representative of the temperature of particular location of testedcomponent 212 over time. The thermographic image data may include, forexample, the wavelength and/or intensity of radiation detected by eachindividual sensor as a function of time. Computing device 226 may beconfigured to receive the thermographic image data from thermal camera218.

The technique of FIG. 11 further includes outputting a representationbased on the thermal response of tested component 212 (248). This stepmay be the similar or substantially the same as the outputting step ofFIG. 9. For example, computing device 226 may process the thermographicimage data received from thermal camera 218 to determine a single valuerepresentative of the thermal response of a location of tested component212 (e.g., represented by a pixel or a set of adjacent pixels) over aduration of time.

In some examples, computing device 226 may be configured to combinethermographic image data from a plurality of thermography tests. In someexamples, outputting a representation based on the thermal response oftested component 212 (248) may include outputting a false color or agrayscale representation of the thermographic image data. In someexamples, computing device 226 may be configured to morph thethermographic image data to substantially align with three-dimensionalmaster data as described above with respect to FIGS. 5-7, and computingdevice 226 may be configured to compare the thermographic image data tothe three-dimensional master data to identify any potentialdeficiencies. In some examples, computing device 26 may be configured toreceive the thermographic image data and flow rate data measured by atleast one flow meter during, prior to, or after the flowing thermographytest, as described above with respect to FIGS. 1-4.

In this way, in some examples, a system may be configured to both cleana tested component and perform flowing thermography on the component ata single testing station. Performing the cleaning and flowingthermography at a single inspection station may be more time and spaceefficient than utilizing two separate stations for the cleaning and theflowing thermography testing. Further, in examples in which gaseous dryice is used to flowing thermography, cleaning and performing flowingthermography substantially simultaneously may be more time efficientthat performing the procedures sequentially.

Although various examples have been described with reference todifferent figures, features of the examples and the examples themselvesmay be combined in various combinations. For example, thetwo-dimensional thermographic image data morphed to substantially alignwith the master image data may include quantitative flowingthermographic image data and/or may include data generated using flowingthermography with gaseous dry ice. As another example, the quantitativeflowing thermographic image data may be determined using thermographicdata generated using dry ice. Other combinations of the techniquesdescribed herein are also contemplated by this disclosure and will beapparent to those of ordinary skill in the art.

In one or more examples, the functions described herein may beimplemented in hardware, software, firmware, or any combination thereof.If implemented in software, the functions may be stored on ortransmitted over, as one or more instructions or code, acomputer-readable medium or computer-readable storage device andexecuted by a hardware-based processing unit. Computer-readable mediamay include computer-readable storage media, which corresponds to atangible medium such as data storage media, or communication mediaincluding any medium that facilitates transfer of a computer programfrom one place to another, e.g., according to a communication protocol.In this manner, computer-readable media generally may correspond to (1)tangible computer-readable storage media or computer-readable storagedevice, which is non-transitory or (2) a communication medium such as asignal or carrier wave. Data storage media may be any available mediathat can be accessed by one or more computers or one or more processorsto retrieve instructions, code and/or data structures for implementationof the techniques described in this disclosure. A computer programproduct may include a computer-readable medium.

By way of example, and not limitation, such computer-readable storagemedia can comprise RAM, ROM, EEPROM, CD-ROM or other optical diskstorage, magnetic disk storage, or other magnetic storage devices, flashmemory, or any other medium that can be used to store desired programcode in the form of instructions or data structures and that can beaccessed by a computer. Also, any connection is properly termed acomputer-readable medium. For example, if instructions are transmittedfrom a website, server, or other remote source using a coaxial cable,fiber optic cable, twisted pair, digital subscriber line (DSL), orwireless technologies such as infrared, radio, and microwave, then thecoaxial cable, fiber optic cable, twisted pair, DSL, or wirelesstechnologies such as infrared, radio, and microwave are included in thedefinition of medium. It should be understood, however, thatcomputer-readable storage media and data storage media do not includeconnections, carrier waves, signals, or other transient media, but areinstead directed to non-transient, tangible storage media. Disk anddisc, as used herein, include compact disc (CD), laser disc, opticaldisc, digital versatile disc (DVD), floppy disk and Blu-ray disc, wheredisks usually reproduce data magnetically, while discs reproduce dataoptically with lasers. Combinations of the above should also be includedwithin the scope of computer-readable media.

Instructions may be executed by one or more processors, such as one ormore digital signal processors (DSPs), general purpose microprocessors,application specific integrated circuits (ASICs), field programmablelogic arrays (FPGAs), or other equivalent integrated or discrete logiccircuitry. Accordingly, the term “processor,” as used herein may referto any of the foregoing structure or any other structure suitable forimplementation of the techniques described herein. In addition, in someaspects, the functionality described herein may be provided withindedicated hardware and/or software modules. Also, the techniques couldbe fully implemented in one or more circuits or logic elements.

The techniques of this disclosure may be implemented in a wide varietyof devices or apparatuses, including a wireless handset, an integratedcircuit (IC) or a set of ICs (e.g., a chip set). Various components,modules, or units are described in this disclosure to emphasizefunctional aspects of devices configured to perform the disclosedtechniques, but do not necessarily require realization by differenthardware units. Rather, as described above, various units may becombined in a hardware unit or provided by a collection ofinteroperative hardware units, including one or more processors asdescribed above, in conjunction with suitable software and/or firmware.

Various examples have been described. These and other examples arewithin the scope of the following claims.

What is claimed is:
 1. A system comprising: a source of dry ice; athermal camera; and a computing device configured to: control the sourceof dry ice to cause dry ice to be introduced into an internal passage ofa tested component, wherein the tested component includes debris withinthe internal passage, and wherein the dry ice removes at least some ofthe debris from the internal passage; receive, from the thermal camera,thermographic image data representative of the thermal response of thetested component; and output a representation based on the thermographicimage data.
 2. The system of claim 1, wherein the thermographic imagedata is representative of the thermal response of the tested componentto the dry ice.
 3. The system of claim 1, further comprising a fluidsource and a valve fluidically coupled to the fluid source, wherein thecomputing device is further configured to control the valve to open apredetermined amount for a predetermined length of time to allow apredetermined pulse of fluid to flow through the internal passage of thetested component, and wherein the thermographic image data isrepresentative of the thermal response of the tested component to thepulse of fluid.
 4. The system of claim 1, wherein the thermographicimage data comprises data representative of thermal response of eachrespective location of a plurality of locations of the tested component,and wherein the computing device is configured to determine a respectivesingle value representative of the thermal response of the component foreach respective location.
 5. The system of claim 4, wherein thecomputing device is configured to output the representation based on thethermographic image data by at least outputting a representation basedon the respective single values.
 6. The system of claim 1, wherein thecomputing device is further configured to: receive master image datarepresentative of a geometry and thermal response of at least one of atheoretical component, a fabricated gold standard component, or anaverage of a plurality of components; morph the thermographic image datato substantially align with the three-dimensional image data and producemorphed thermographic image data; and wherein the computing device isconfigured to output the representation based on the thermographic imagedata by at least outputting a representation based on the morphedthermographic image data for display.
 7. The system of claim 1, whereinthe computing device is further configured to: receive flow rate valuesfrom the at least one flow meter relating to flow testing of a firstcomponent fluidically coupled to the plenum; and associate the flow ratevalues with the thermographic image data to produce quantitative flowingthermographic image data.
 8. A method comprising: controlling, by acomputing device, a source of dry ice to cause dry ice to be introducedinto an internal passage of a tested component, wherein the testedcomponent includes debris within the internal passage, and wherein thedry ice removes at least some of the debris from the internal passage;receiving, by the computing device, from a thermal camera, thermographicimage data representative of the thermal response of the testedcomponent; and outputting, by the computing device, a representationbased on the thermographic image data.
 9. The method of claim 8, whereinthe thermographic image data is representative of the thermal responseof the tested component to the dry ice.
 10. The method of claim 8,further comprising controlling, by the computing device, a valvefluidically coupled to a fluid source to open a predetermined amount fora predetermined length of time to allow a predetermined pulse of fluidto flow through the internal passage of the tested component, andwherein the thermographic image data is representative of the thermalresponse of the tested component to the pulse of fluid.
 11. The methodof claim 8, wherein the thermographic image data comprises datarepresentative of thermal response of each respective location of aplurality of locations of the tested component, and further comprisingdetermining, by the computing device, a respective single valuerepresentative of the thermal response of the component for eachrespective location.
 12. The method of claim 11, wherein outputting therepresentation based on the thermographic image data comprisesoutputting a representation based on the respective single values. 13.The method of claim 8, further comprising: receiving, by the computingdevice, master image data representative of a geometry and thermalresponse of at least one of a theoretical component, a fabricated goldstandard component, or an average of a plurality of components;morphing, by the computing device, the thermographic image data tosubstantially align with the three-dimensional image data and producemorphed thermographic image data; and wherein outputting therepresentation based on the thermographic image data comprisesoutputting a representation based on the morphed thermographic imagedata for display.
 14. The method of claim 8, further comprising:receiving, by the computing device, flow rate values from the at leastone flow meter relating to flow testing of a first component fluidicallycoupled to the plenum; and associating, by the computing device, theflow rate values with the thermographic image data to producequantitative flowing thermographic image data.
 15. A computer readablestorage medium comprising instructions that, when executed, cause atleast one processor to: control a source of dry ice to cause dry ice tobe introduced into an internal passage of a tested component, whereinthe tested component includes debris within the internal passage, andwherein the dry ice removes at least some of the debris from theinternal passage; receive, from a thermal camera, thermographic imagedata representative of the thermal response of the tested component; andoutput a representation based on the thermographic image data.
 16. Thecomputer readable storage medium of claim 15, wherein the thermographicimage data is representative of the thermal response of the testedcomponent to the dry ice.
 17. The computer readable storage medium ofclaim 15, further comprising instructions that, when executed, cause theat least one processor to control a valve fluidically coupled to a fluidsource to open a predetermined amount for a predetermined length of timeto allow a predetermined pulse of fluid to flow through the internalpassage of the tested component, and wherein the thermographic imagedata is representative of the thermal response of the tested componentto the pulse of fluid.
 18. The computer readable storage medium of claim15, wherein the thermographic image data comprises data representativeof thermal response of each respective location of a plurality oflocations of the tested component, and further comprising instructionsthat, when executed, cause the at least one processor to determine arespective single value representative of the thermal response of thecomponent for each respective location.
 19. The computer readablestorage medium of claim 15, further comprising instructions that, whenexecuted, cause the at least one processor to: receive master image datarepresentative of a geometry and thermal response of at least one of atheoretical component, a fabricated gold standard component, or anaverage of a plurality of components; morph the thermographic image datato substantially align with the three-dimensional image data and producemorphed thermographic image data; and wherein the instructions that,when executed, cause the at least one processor to output therepresentation based on the thermographic image data compriseinstructions that, when executed, cause the at least one processor tooutput a representation based on the morphed thermographic image datafor display.
 20. The computer readable storage medium of claim 15,further comprising instructions that, when executed, cause the at leastone processor to: receive flow rate values from the at least one flowmeter relating to flow testing of a first component fluidically coupledto the plenum; and associate the flow rate values with the thermographicimage data to produce quantitative flowing thermographic image data.